Theory and development of COMPUTER SYSTEMS which perform tasks that normally require human intelligence. Such tasks may include speech recognition, LEARNING; VISUAL PERCEPTION; MATHEMATICAL COMPUTING; reasoning, PROBLEM SOLVING, DECISION-MAKING, and translation of language.
The ability to learn and to deal with new situations and to deal effectively with tasks involving abstractions.
Computer programs based on knowledge developed from consultation with experts on a problem, and the processing and/or formalizing of this knowledge using these programs in such a manner that the problems may be solved.
Approximate, quantitative reasoning that is concerned with the linguistic ambiguity which exists in natural or synthetic language. At its core are variables such as good, bad, and young as well as modifiers such as more, less, and very. These ordinary terms represent fuzzy sets in a particular problem. Fuzzy logic plays a key role in many medical expert systems.
A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming.
Toxic, possibly carcinogenic, monomer of neoprene, a synthetic rubber; causes damage to skin, lungs, CNS, kidneys, liver, blood cells and fetuses. Synonym: 2-chlorobutadiene.
Use of an interactive computer system designed to assist the physician or other health professional in choosing between certain relationships or variables for the purpose of making a diagnostic or therapeutic decision.
Standardized tests that measure the present general ability or aptitude for intellectual performance.
Application of computer programs designed to assist the physician in solving a diagnostic problem.
The ability to understand and manage emotions and to use emotional knowledge to enhance thought and deal effectively with tasks. Components of emotional intelligence include empathy, self-motivation, self-awareness, self-regulation, and social skill. Emotional intelligence is a measurement of one's ability to socialize or relate to others.
A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.
Computer-based representation of physical systems and phenomena such as chemical processes.
Tests designed to measure intellectual functioning in children and adults.
Sequential operating programs and data which instruct the functioning of a digital computer.
Intellectual or mental process whereby an organism obtains knowledge.
An individual intelligence test designed primarily for school children to predict school performance and the ability to adjust to everyday demands.
Tests designed to assess neurological function associated with certain behaviors. They are used in diagnosing brain dysfunction or damage and central nervous system disorders or injury.
Disturbances in mental processes related to learning, thinking, reasoning, and judgment.
The continuous sequential physiological and psychological maturing of an individual from birth up to but not including ADOLESCENCE.
Subnormal intellectual functioning which originates during the developmental period. This has multiple potential etiologies, including genetic defects and perinatal insults. Intelligence quotient (IQ) scores are commonly used to determine whether an individual has an intellectual disability. IQ scores between 70 and 79 are in the borderline range. Scores below 67 are in the disabled range. (from Joynt, Clinical Neurology, 1992, Ch55, p28)
A learning situation involving more than one alternative from which a selection is made in order to attain a specific goal.
A set of cognitive functions that controls complex, goal-directed thought and behavior. Executive function involves multiple domains, such as CONCEPT FORMATION, goal management, cognitive flexibility, INHIBITION control, and WORKING MEMORY. Impaired executive function is seen in a range of disorders, e.g., SCHIZOPHRENIA; and ADHD.
Works containing information articles on subjects in every field of knowledge, usually arranged in alphabetical order, or a similar work limited to a special field or subject. (From The ALA Glossary of Library and Information Science, 1983)
A plan for collecting and utilizing data so that desired information can be obtained with sufficient precision or so that an hypothesis can be tested properly.
NATIONAL LIBRARY OF MEDICINE service for health professionals and consumers. It links extensive information from the National Institutes of Health and other reviewed sources of information on specific diseases and conditions.
Writings having excellence of form or expression and expressing ideas of permanent or universal interest. The body of written works produced in a particular language, country, or age. (Webster, 3d ed)
The aggregate of various economic, political, and social policies by which an imperial power maintains or extends its control over other areas or peoples. It includes the practice of or belief in acquiring and retaining colonies. The emphasis is less on its identity as an ideological political system than on its designation in a period of history. (Webster, 3d ed; from Dr. J. Cassedy, NLM History of Medicine Division)
Those affective states which can be experienced and have arousing and motivational properties.
The faculty of expressing the amusing, clever, or comical or the keen perception and cleverly apt expression of connections between ideas that awaken amusement and pleasure. (From Random House Unabridged Dictionary, 2d ed)
A legal concept that an accused is not criminally responsible if, at the time of committing the act, the person was laboring under such a defect of reason from disease of the mind as not to know the nature and quality of the act done or if the act was known, to not have known that what was done was wrong. (From Black's Law Dictionary, 6th ed)

E-CELL: software environment for whole-cell simulation. (1/4007)

MOTIVATION: Genome sequencing projects and further systematic functional analyses of complete gene sets are producing an unprecedented mass of molecular information for a wide range of model organisms. This provides us with a detailed account of the cell with which we may begin to build models for simulating intracellular molecular processes to predict the dynamic behavior of living cells. Previous work in biochemical and genetic simulation has isolated well-characterized pathways for detailed analysis, but methods for building integrative models of the cell that incorporate gene regulation, metabolism and signaling have not been established. We, therefore, were motivated to develop a software environment for building such integrative models based on gene sets, and running simulations to conduct experiments in silico. RESULTS: E-CELL, a modeling and simulation environment for biochemical and genetic processes, has been developed. The E-CELL system allows a user to define functions of proteins, protein-protein interactions, protein-DNA interactions, regulation of gene expression and other features of cellular metabolism, as a set of reaction rules. E-CELL simulates cell behavior by numerically integrating the differential equations described implicitly in these reaction rules. The user can observe, through a computer display, dynamic changes in concentrations of proteins, protein complexes and other chemical compounds in the cell. Using this software, we constructed a model of a hypothetical cell with only 127 genes sufficient for transcription, translation, energy production and phospholipid synthesis. Most of the genes are taken from Mycoplasma genitalium, the organism having the smallest known chromosome, whose complete 580 kb genome sequence was determined at TIGR in 1995. We discuss future applications of the E-CELL system with special respect to genome engineering. AVAILABILITY: The E-CELL software is available upon request. SUPPLEMENTARY INFORMATION: The complete list of rules of the developed cell model with kinetic parameters can be obtained via our web site at: http://e-cell.org/.  (+info)

A prognostic computer model to individually predict post-procedural complications in interventional cardiology: the INTERVENT Project. (2/4007)

AIMS: The purpose of this part of the INTERVENT project was (1) to redefine and individually predict post-procedural complications associated with coronary interventions, including alternative/adjunctive techniques to PTCA and (2) to employ the prognostic INTERVENT computer model to clarify the structural relationship between (pre)-procedural risk factors and post-procedural outcome. METHODS AND RESULTS: In a multicentre study, 2500 data items of 455 consecutive patients (mean age: 61.1+/-8.3 years: 33-84 years) undergoing coronary interventions at three university centres were analysed. 80.4% of the patients were male, 16.7% had unstable angina, and 5.1%/10.1% acute/subacute myocardial infarction. There were multiple or multivessel stenoses in 16.0%, vessel bending >90 degrees in 14.5%, irregular vessel contours in 65.0%, moderate calcifications in 20.9%, moderate/severe vessel tortuosity in 53.2% and a diameter stenosis of 90%-99% in 44.4% of cases. The in-lab (out-of-lab) complications were: 0.4% (0.9%) death, 1.8% (0.2%) abrupt vessel closure with myocardial infarction and 5.5% (4.0) haemodynamic disorders. CONCLUSION: Computer algorithms derived from artificial intelligence were able to predict the individual risk of these post-procedural complications with an accuracy of >95% and to explain the structural relationship between risk factors and post-procedural complications. The most important prognostic factors were: heart failure (NYHA class), use of adjunctive/alternative techniques (rotablation, atherectomy, laser), acute coronary ischaemia, pre-existent cardiac medication, stenosis length, stenosis morphology (calcification), gender, age, amount of contrast agent and smoker status. Pre-medication with aspirin or other cardiac medication had a beneficial effect. Techniques, such as laser angioplasty or atherectomy were predictors for post-procedural complications. Single predictors alone were not able to describe the individual outcome completely.  (+info)

Virtual management of radiology examinations in the virtual radiology environment using common object request broker architecture services. (3/4007)

In the Department of Defense (DoD), US Army Medical Command is now embarking on an extremely exciting new project--creating a virtual radiology environment (VRE) for the management of radiology examinations. The business of radiology in the military is therefore being reengineered on several fronts by the VRE Project. In the VRE Project, a set of intelligent agent algorithms determine where examinations are to routed for reading bases on a knowledge base of the entire VRE. The set of algorithms, called the Meta-Manager, is hierarchical and uses object-based communications between medical treatment facilities (MTFs) and medical centers that have digital imaging network picture archiving and communications systems (DIN-PACS) networks. The communications is based on use of common object request broker architecture (CORBA) objects and services to send patient demographics and examination images from DIN-PACS networks in the MTFs to the DIN-PACS networks at the medical centers for diagnosis. The Meta-Manager is also responsible for updating the diagnosis at the originating MTF. CORBA services are used to perform secure message communications between DIN-PACS nodes in the VRE network. The Meta-Manager has a fail-safe architecture that allows the master Meta-Manager function to float to regional Meta-Manager sites in case of server failure. A prototype of the CORBA-based Meta-Manager is being developed by the University of Arizona's Computer Engineering Research Laboratory using the unified modeling language (UML) as a design tool. The prototype will implement the main functions described in the Meta-Manager design specification. The results of this project are expected to reengineer the process of radiology in the military and have extensions to commercial radiology environments.  (+info)

Meta-manager: a requirements analysis. (4/4007)

The digital imaging network-picture-archiving and communications system (DIN-PACS) will be implemented in ten sites within the Great Plains Regional Medical Command (GPRMC). This network of PACS and teleradiology technology over a shared T1 network has opened the door for round the clock radiology coverage of all sites. However, the concept of a virtual radiology environment poses new issues for military medicine. A new workflow management system must be developed. This workflow management system will allow us to efficiently resolve these issues including quality of care, availability, severe capitation, and quality of the workforce. The design process of this management system must employ existing technology, operate over various telecommunication networks and protocols, be independent of platform operating systems, be flexible and scaleable, and involve the end user at the outset in the design process for which it is developed. Using the unified modeling language (UML), the specifications for this new business management system were created in concert between the University of Arizona and the GPRMC. These specifications detail a management system operating through a common object request brokered architecture (CORBA) environment. In this presentation, we characterize the Meta-Manager management system including aspects of intelligence, interfacility routing, fail-safe operations, and expected improvements in patient care and efficiency.  (+info)

Integrated radiology information system, picture archiving and communications system, and teleradiology--workflow-driven and future-proof. (5/4007)

The proliferation of integrated radiology information system/picture archiving and communication system (RIS/PACS) and teleradiology has been slow because of two concerns: usability and economic return. A major dissatisfaction on the usability issue is that contemporary systems are not intelligent enough to support the logical workflow of radiologists. We propose to better understand the algorithms underlying the radiologists' reading process, and then embed this intelligence into the software program so that radiologists can interact with the system with less conscious effort. Regarding economic return issues, people are looking for insurance against obsolescence in order to protect their investments. We propose to future-proof a system by sticking to the following principles: compliance to industry standards, commercial off-the-shelf (COTS) components, and modularity. An integrated RIS/PACS and teleradiology system designed to be workflow-driven and future-proof is being developed at Texas Tech University Health Sciences Center.  (+info)

Mapping of putative binding sites on the ectodomain of the type II TGF-beta receptor by scanning-deletion mutagenesis and knowledge-based modeling. (6/4007)

Binding surfaces of the type II transforming growth factor (TGF)-beta receptor extracellular domain (TbetaRII-ECD) are mapped by combining scanning-deletion mutagenesis results with knowledge-based modeling of the ectodomain structure. Of the 17 deletion mutants produced within the core binding domain of TbetaRII-ECD, only three retained binding to TGF-beta. Comparative modeling based on the crystal structure of the activin type II receptor extracellular domain (ActRII-ECD) indicates that the TbetaRII mutants which retain TGF-beta binding are deleted in some of the loops connecting the beta-strands in the TbetaRII-ECD model. Interpretation of the mutagenesis data within the structural framework of the ectodomain model allows for the prediction of potential binding sites at the surface of TbetaRII-ECD.  (+info)

Integrated databases and computer systems for studying eukaryotic gene expression. (7/4007)

MOTIVATION: The goal of the work was to develop a WWW-oriented computer system providing a maximal integration of informational and software resources on the regulation of gene expression and navigation through them. Rapid growth of the variety and volume of information accumulated in the databases on regulation of gene expression necessarily requires the development of computer systems for automated discovery of the knowledge that can be further used for analysis of regulatory genomic sequences. RESULTS: The GeneExpress system developed includes the following major informational and software modules: (1) Transcription Regulation (TRRD) module, which contains the databases on transcription regulatory regions of eukaryotic genes and TRRD Viewer for data visualization; (2) Site Activity Prediction (ACTIVITY), the module for analysis of functional site activity and its prediction; (3) Site Recognition module, which comprises (a) B-DNA-VIDEO system for detecting the conformational and physicochemical properties of DNA sites significant for their recognition, (b) Consensus and Weight Matrices (ConsFrec) and (c) Transcription Factor Binding Sites Recognition (TFBSR) systems for detecting conservative contextual regions of functional sites and their recognition; (4) Gene Networks (GeneNet), which contains an object-oriented database accumulating the data on gene networks and signal transduction pathways, and the Java-based Viewer for exploration and visualization of the GeneNet information; (5) mRNA Translation (Leader mRNA), designed to analyze structural and contextual properties of mRNA 5'-untranslated regions (5'-UTRs) and predict their translation efficiency; (6) other program modules designed to study the structure-function organization of regulatory genomic sequences and regulatory proteins. AVAILABILITY: GeneExpress is available at http://wwwmgs.bionet.nsc. ru/systems/GeneExpress/ and the links to the mirror site(s) can be found at http://wwwmgs.bionet.nsc.ru/mgs/links/mirrors.html+ ++.  (+info)

Automated diagnosis of data-model conflicts using metadata. (8/4007)

The authors describe a methodology for helping computational biologists diagnose discrepancies they encounter between experimental data and the predictions of scientific models. The authors call these discrepancies data-model conflicts. They have built a prototype system to help scientists resolve these conflicts in a more systematic, evidence-based manner. In computational biology, data-model conflicts are the result of complex computations in which data and models are transformed and evaluated. Increasingly, the data, models, and tools employed in these computations come from diverse and distributed resources, contributing to a widening gap between the scientist and the original context in which these resources were produced. This contextual rift can contribute to the misuse of scientific data or tools and amplifies the problem of diagnosing data-model conflicts. The authors' hypothesis is that systematic collection of metadata about a computational process can help bridge the contextual rift and provide information for supporting automated diagnosis of these conflicts. The methodology involves three major steps. First, the authors decompose the data-model evaluation process into abstract functional components. Next, they use this process decomposition to enumerate the possible causes of the data-model conflict and direct the acquisition of diagnostically relevant metadata. Finally, they use evidence statically and dynamically generated from the metadata collected to identify the most likely causes of the given conflict. They describe how these methods are implemented in a knowledge-based system called GRENDEL and show how GRENDEL can be used to help diagnose conflicts between experimental data and computationally built structural models of the 30S ribosomal subunit.  (+info)

TY - GEN. T1 - Performance comparison of machine learning classification algorithms. AU - Veena, K. M.. AU - Manjula Shenoy, K.. AU - Ajitha Shenoy, K. B.. PY - 2018/1/1. Y1 - 2018/1/1. N2 - Classification of binary and multi-class datasets to draw meaningful decisions is the key in todays scientific world. Machine learning algorithms are known to effectively classify complex datasets. This paper attempts to study and compare the classification performance if four supervised machine learning classification algorithms, viz., Classification And Regression Trees, k-Nearest Neighbor, Support Vector Machines and Naive Bayes to five different types of data sets, viz., mushrooms, page-block, satimage, thyroid and wine. The classification accuracy of each algorithm is evaluated using the 10-fold cross-validation technique. The Classification And Regression Tree algorithm is found to give the best classification accuracy.. AB - Classification of binary and multi-class datasets to draw meaningful ...
Artificial intelligence can make doctors more efficient by diagnosing a patient quickly without any loss of accuracy, it can even interpret results rapidly. But despite all these benefits, we shouldnt forget that artificial intelligence is but another piece of technology. And like all pieces of technology, there will always be a risk of failure.. Now, the question at hand is whether artificial intelligence can be sued when it causes injury or death to a patient. How is justice meted in such a scenario, and who is liable for damages?. No Laws, No Precedents On Handling AI.. As of this writing, there are no known laws or precedents that govern the use of artificial intelligence as the technology has yet to be implemented into the medical field. However, this does not mean that when an injury is caused by the failure of artificial intelligence, that there are no liabilities to be determined.. However.. Artificial intelligence should be treated as a product rather than its own person, given the ...
Agent--Based Models (ABMs) are indispensable to studying the aggregated impacts of individual actions of heterogeneous interacting adaptive agents. Concurrently, artificial intelligence has been employed for decades to simulate autonomous actions of individual entities that react, learn and exchange information with an environment and one another. There are obvious synergies between the two computational approaches. For example, artificial intelligence is often used to enhance agents behaviour in ABMs. Artificial intelligence learning algorithms (AILAs) allow for a richer agents architecture for operationalization of more realistic learning decisions beyond a simplistic treatment of agents cognitive and sensory capacities. Firstly, we review recent socio--economic and spatial ABMs that employ different AILAs to create individually, socially and spatially intelligent agents. We provide a systematic structured analysis of the types of AILAs employed in various application domains, their specific
As a MarketResearchReports.Biz report, it covers all details inside analysis and opinion in Artificial Intelligence Market. This report mainly introduces volume and value market share by players, by regions, by product type, by consumers and also their price change details.. This report splits Artificial Intelligence Market by Product & Service, by Test Type, by Allergen, which covers the history data information from 2016 to 2024.. The Artificial Intelligence Market report provides analysis of the global artificial intelligence market for the period 2014-2024, wherein the years from 2016 to 2024 is the forecast period and 2015 is considered as the base year. The report precisely covers all the major trends and technologies playing a major role in the artificial intelligence markets growth over the forecast period. It also highlights the drivers, restraints, and opportunities expected to influence the market growth during this period. The study provides a holistic perspective on the ...
Get Free Sample Global Healthcare Artificial Intelligence Market Report 2019″ at: https://www.marketresearchfuture.com/sample_request/5681. Top Companies Operating in Healthcare Artificial Intelligence Market. The prominent players operating the Artificial Intelligence in Healthcare market are Koninklijke Philips N.V., IBM Watson Health, NVIDIA Corporation, CloudMedx Inc., Microsoft Corporation, Google, General Electric, Next IT Corp., Intel Corporation, DEEP GENOMICS, General Vision, and Stryker.. Healthcare Artificial Intelligence Market Potential and Pitfalls. Artificial Intelligence has developed several applications in the healthcare sector, such as delivery of health services, detection of diseases, drug discovery, and management of chronic diseases. It ensures effectiveness and efficiency which is likely to trigger its adoption rate in the coming years. AI has also strengthened its foothold in the healthcare research sector for delivering accurate results. This has further contributed ...
Purpose This paper proposes a real-time knowledge support framework for the development of an RFID-multi-agent based process knowledge-based system which has the ability to solve dynamic logistics process management problems. Design/methodology/approach The proposed system is developed with real-time process management capability which automatically identifies current process status, performs the process logic checking/reasoning, and, provides process knowledge support to staff members when they are tackling logistics activity problems. The unique feature of this on-line knowledge-based system, which enables it to enhance the performance of logistics organizations, is a process management engine incorporating radio-frequency identification (RFID) and multi-agent (MA) technologies.
With the great advancement in robot technology, smart human-robot interaction is considered to be the most wanted success by the researchers these days. If a robot can identify emotions and intentions of a human interacting with it, that would make robots more useful. Electroencephalography (EEG) is considered one effective way of recording emotions and motivations of a human using brain. Various machine learning techniques are used successfully to classify EEG data accurately. K-Nearest Neighbor, Bayesian Network, Artificial Neural Networks and Support Vector Machine are among the suitable machine learning techniques to classify EEG data. The aim of this thesis is to evaluate different machine learning techniques to classify EEG data associated with specific affective/emotional states. Different methods based on different signal processing techniques are studied to find a suitable method to process the EEG data. Various number of EEG data features are used to identify those which give best ...
TY - GEN. T1 - Weka machine learning classification in identifying autonomic dysfunction parameters associated with ACE insertion/deletion genotypes. AU - Ng, Ethan. AU - Hambly, Brett. AU - Matthews, Slade. AU - McLachlan, Craig S.. AU - Jelinek, Herbert F.. PY - 2012/7/16. Y1 - 2012/7/16. N2 - This study was designed to investigate parameters of autonomic dysfunction that may be under the influence of ACE ID genotypes. 136 patients with (47) and without type II diabetes were genotyped. Biomarkers such as HbAlc and eGFR, blood pressure, blood cholesterol are in part regulated by the autonomic nervous system and heart rate variability is an indicator of autonomic balance between the sympathetic and parasympathetic division. Several statistical methods were used, including the J48 decision tree machine learning algorithm to associate parameters of autonomic dysfunction and other biomarkers with ACE genotype. Non-parametric and machine learning methods detected more variables, which were able to ...
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Research of the Section for Artificial Intelligence and Decision Support (AID) focusses on Artificial Intelligence technology and computer-based decison support and its use in the medical domain. This includes the development of software systems for intelligent data analysis, knowledge-based systems technology for decision support and therapy planning, and natural language processing which deals with automatic processing of text and speech.. The department offers lectures in Artificial Intelligence on an introductory as well as an advanced level. With regard to particular study programmes, we offer courses for students of Medicine and of Medical Informatics, as well as for students of the Middle European Master Programme in Cognitive Science. Courses are also offered for computer science students in a cooperation with the University of Vienna.. The department was founded in 1977 as an institute of the Medical Faculty of the University of Vienna. In 2004, it became part of the Center for Brain ...
Leen dit bij een bibliotheek! Artificial intelligence in medicine : 14th Conference on Artificial Intelligence in Medicine, AIME 2013, Murcia, Spain, May 29-June 1, 2013 : proceedings. [Niels Peek; Roque Marín Morales; Mor Peleg;] -- This book constitutes the refereed proceedings of the 14th Conference on Artificial Intelligence in Medicine, AIME 2013, held in Murcia, Spain, in May/June 2013. The 43 revised full and short papers ...
Engineering & Artificial Intelligence Projects for $10 - $30. There are two artificial intelligence homework. Homework-3 has 6 questions and Homework-4 has 4 questions. The artificial intelligence homework will send with message. Payment will be done after home...
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In this chapter we provide a survey of protein secondary and supersecondary structure prediction using methods from machine learning. Our focus is on machine learning methods applicable to β-hairpin and β-sheet prediction, but we also discuss methods for more general supersecondary structure prediction. We provide background on the secondary and supersecondary structures that we discuss, the features used to describe them, and the basic theory behind the machine learning methods used. We survey the machine learning methods available for secondary and supersecondary structure prediction and compare them where possible.. ...
The challenge with artificial intelligence is that no single and agreed-upon definition exists. Nils Nilsson defined A.I. as activity devoted to making machines intelligent, and intelligence is that quality that enables an entity to function appropriately and with foresight in its environment. But that definition isnt close to describing how A.I. evolved.. Artificial intelligence began with the Turing Test, proposed in 1950 by Alan Turing, the scientist, cryptanalyst and theoretical biologist. Since then, rapid progress has been made over the last 75 years, advancing A.I. capabilities.. Isaac Asimov proposed the Three Laws of Robotics in 1950. The first A.I. program was coded in 1951. In 1959, MIT began research in the field of artificial intelligence. GM introduced the first robot into its production assembly line in 1961. The 1960s were transformative, with the first machine learning program written and the first demonstration of an A.I. program which understood natural language, and the ...
On the basis of offering, the global artificial intelligence in healthcare market is segmented into hardware, software, and services. The market is further segmented by technology into speech recognition, machine learning, querying method, natural language processing, and context aware processing; by application into medical research, diagnosing diseases, electrocardiography, laparoscopy, medical imaging, personalized health assessments, drug discovery, personalized medicine, and others and by end-users into diagnostic labs, hospitals, clinics, and others.. The global artificial intelligence in healthcare market is anticipated to record a CAGR of 45.3% over the forecast period i.e. 2019-2027.. Artificial intelligence in healthcare is being used in radiology, imaging, electronic health records and others which can be attributed to its low error rate, high speed, accuracy, precision and ability to complete a hazardous task without the involvement of humans. For instance, mishandling of samples for ...
Applying Artificial Intelligence to Financial Investing: 10.4018/978-1-5225-2255-3.ch001: Artificial intelligence techniques have long been applied to financial investing scenarios to determine market inefficiencies, criteria for credit scoring
Peptides are routinely identified from mass spectrometry-based proteomics experiments by matching observed spectra to peptides derived from protein databases. The error rates of these identifications can be estimated by target-decoy analysis, which involves matching spectra to shuffled or reversed peptides. Besides estimating error rates, decoy searches can be used by semi-supervised machine learning algorithms to increase the number of confidently identified peptides. As for all machine learning algorithms, however, the results must be validated to avoid issues such as overfitting or biased learning, which would produce unreliable peptide identifications. Here, we discuss how the target-decoy method is employed in machine learning for shotgun proteomics, focusing on how the results can be validated by cross-validation, a frequently used validation scheme in machine learning. We also use simulated data to demonstrate the proposed cross-validation schemes ability to detect overfitting.. ...
Purpose: The study is conducted to evaluate the adaptability of artificial intelligence in recruitment and to assess the effect of this technology on the performance of the employees. Design/Methodology/Approach: Standard Multiple Linear regression model is used to predict the performance of the employees and one-way ANOVA is used to compare the artificial intelligence based recruitment with performance indicating variables namely reliability, productivity, Automation, Gamification & Training using SPSS. Snowball sampling method has been adopted for a sample size of 440 respondents working in leading recruitment consultancies in urban Bangalore. Findings: There is a greater association between the recruitment and performance variables when artificial intelligence is adopted as it is significant at 0.001 per cent level and productivity being the maximum. However, the impact of implementing gamification for recruitment doesnt have a significant impact on the output due to partial significant
Get information, facts, and pictures about artificial intelligence at Encyclopedia.com. Make research projects and school reports about artificial intelligence easy with credible articles from our FREE, online encyclopedia and dictionary.
European CEO: How are you analysing all of this genetic data?. Niels Iversen Møller: Well were using artificial intelligence and supercomputers to analyse the genomes of humans or bacteria. We have trained the artificial intelligence to identify components that are unique to cancer patients, and also the Achilles heel proteins of the pathogens that were analysing.. When we talk about cancer, there are certain components called epitopes that we identify by comparing the DNA from tumours to the DNA of healthy tissue. By looking at differences between cancer DNA and also healthy DNA, we can find the mutations that are critical. And also critical in terms of formulating into a vaccine.. When we talk about bacteria, we again analyse using our artificial intelligence. The DNA of those bacteria, finding the Achilles heel components really in the bacteria that we want to put into a vaccine to illicit a strong and protective immune response.. European CEO: So this is personalised healthcare right down ...
TUESDAY, April 25, 2017 (HealthDay News) -- It may be possible to use artificial intelligence to diagnose tuberculosis in people who live in developing nations, a new study suggests.. TB, among the top 10 causes of death worldwide, can be identified on X-rays. But, the expertise required to screen for and diagnose TB is often lacking in areas that have high rates of the lung disease, according to the studys authors.. The researchers from Thomas Jefferson University in Philadelphia used 1,007 X-rays of people with and without active TB to train artificial intelligence models to identify TB on X-rays. It proved highly accurate -- up to 96 percent-- in diagnosing cases.. The study findings were published online April 25 in the journal Radiology. An artificial intelligence solution that could interpret radiographs for presence of TB in a cost-effective way could expand the reach of early identification and treatment in developing nations, study co-author Dr. Paras Lakhani, an assistant professor ...
Artificial Intelligence is already impacting our lives in a major way. Be it getting driving instructions through our smart phone or getting daily reminders by our fitness device to increase our workouts, all these are manifestations of how Artificial Intelligence is changing the way we function. What is often less understood is the significant role Artificial Intelligence can play in the social sector.
View Notes - Homework1 from ENGL 135 at DeVry Addison. Ginger Binder Artificial Intelligence Homework #1 1. Researching and examining various artificial intelligence articles on the subject
How is Mcculloch-Pitts Neuron Model (artificial intelligence) abbreviated? M-P stands for Mcculloch-Pitts Neuron Model (artificial intelligence). M-P is defined as Mcculloch-Pitts Neuron Model (artificial intelligence) very rarely.
BACKGROUND: Driven by the rapid development of big data and processing power, artificial intelligence and machine learning (ML) applications are poised to expand orthopedic surgery frontiers. Lower extremity arthroplasty is uniquely positioned to most dramatically benefit from ML applications given its central role in alternative payment models and the value equation. METHODS: In this report, we discuss the origins and model specifics behind machine learning, consider its progression into healthcare, and present some of its most recent advances and applications in arthroplasty. RESULTS: A narrative review of artificial intelligence and ML developments is summarized with specific applications to lower extremity arthroplasty, with specific lessons learned from osteoarthritis gait models, joint-specific imaging analysis, and value-based payment models. CONCLUSION: The advancement and employment of ML provides an opportunity to provide data-driven, high performance medicine that can rapidly improve the
Published in Knowledge-Based Systems, 2017. Recommended citation: María Pérez-Ortiz, Pedro Antonio Gutiérrez, M. D. Ayllón-Terán, N. Heaton, R. Ciria, J. Briceño, César Hervás-Martínez, Synthetic semi-supervised learning in imbalanced domains: Constructing a model for donor-recipient matching in liver transplantation. Knowledge-Based Systems, Vol. 123, 2017, pp.75--87. http://doi.org/10.1016/j.knosys.2017.02.020 ...
The mission of the CI group in our Department is to perform research on various aspects of computational intelligence and to contribute to the Business Mathematics and Informatics curriculum. Computational Intelligence belongs to the areas of evolutionary computing, fuzzy computing and neurocomputing. As opposed to traditional logic based artificial intelligence techniques, computational intelligence techniques are generally bottom-up, where order and structure emerges from an unstructured beginning ...
Intelligent systems can optimise their structure and properties in order to successfully function within a complex, partially changing environment. Three sub-areas - perception, learning and action - can be differentiated here. The scientists at the Max Planck Institute for Intelligent Systems are carrying out basic research and development of intelligent systems in all three sub-areas. Research expertise in the areas of computer science, material science and biology is brought together in one Institute, at two different sites.
An Analytical Study on Performance Factors of Automatic Classification based on Machine Learning - automatic classification;text categorization;performance factors;conference paper;rocchio algorithm;multi-label classification;machine learning;
Artificial Intelligence can not only turn your customer data into business insights but can use that information to make intelligent decisions, predict outcomes, suggest actions and automate tasks based on machine learning. AI makes your business smarter about how and when it engages its customers. Artificial intelligence is a game-changing business technology thats transforming how we work.
Artificial Intelligence can not only turn your customer data into business insights but can use that information to make intelligent decisions, predict outcomes, suggest actions and automate tasks based on machine learning. AI makes your business smarter about how and when it engages its customers. Artificial intelligence is a game-changing business technology thats transforming how we work.
Machine learning is a branch of artificial intelligence science i.e. the systems that can learn data. For example, a machine learning sys...
MACHINE LEARNING Adversarial attacks on medical machine. THE PAPERS The Workshop on Machine Learning in Medical Applications was held on July 15th, 1999 at Chania, Island of Crete, in Greece, and aimed at presenting some of the advances that have been achieved in the field of application of ML methods in medicine., Machine Learning in Medical Imaging. Download Call for Papers (PDF). Machine learning plays an essential role in the field of medical imaging and image informatics. With advances in medical imaging, new machine learning methods and applications are demanded. Due to large variation and complexity, it is necessary to learn representations of. Machine learning will improve the radiology patient experience, at every step. Much of the initial focus for the application of machine learning in medical imaging has been on image analysis and developing tools to make radiologists more efficient and productive. The … Nov 16, 2018 · The measurements in this Machine Learning applications ...
Functional networks play an important role in the analysis of biological processes and systems. The inference of these networks from high-throughput (-omics) data is an area of intense research. So far, the similarity-based inference paradigm (e.g. gene co-expression) has been the most popular approach. It assumes a functional relationship between genes which are expressed at similar levels across different samples. An alternative to this paradigm is the inference of relationships from the structure of machine learning models. These models are able to capture complex relationships between variables, that often are different/complementary to the similarity-based methods. We propose a protocol to infer functional networks from machine learning models, called FuNeL. It assumes, that genes used together within a rule-based machine learning model to classify the samples, might also be functionally related at a biological level. The protocol is first tested on synthetic datasets and then evaluated on a test
by Matthew Lynch, Tech Edvocate. For years, educators have struggled to help each and every student with their individualized educational needs. That gets incredibly tough in a classroom of twenty, thirty, forty, or fifty students all required to pass the same standardized test, regardless of personal growth. The use of artificial intelligence has the potential to disrupt the traditional and potentially damaging one-size-fits all model of modern teaching. Machine Learning algorithms have already begun helping teachers fill the gaps while indicating which subjects students are struggling with the most. If you think AI and chalkboards dont go hand-in-hand, well prove you wrong with five examples of classroom-based Artificial Intelligence.. http://www.thetechedvocate.org/5-examples-artificial-intelligence-classroom/. Share on Facebook ...
please accept our apologies for cross-posting] ========================================== Call For Papers - Special Issue Submission Due Date: June 30, 2010 Special Issue On Medical Diagnosis Systems Guest Editors: - Alejandro Rodr guez-Gonz lez (Universidad Carlos III de Madrid, Spain) - Miguel Angel Mayer (Barcelona Medical Association, Spain) Introduction ,From the early 1970s, several diagnosis systems were introduced to assist physicians in the diagnosis process. Most of these systems were focused on concrete artificial intelligence techniques related to statistics and probabilistic-like Bayesian networks, probabilistic reasoning, and so forth. Today, there are several new artificial intelligence techniques that can be fully exploited to help the research and development of clinical decision support systems oriented to diagnosis. This diagnosis process can be of several types depending on the scope that appears to be covered: from the diagnosis of very concrete pathologies to the diagnosis ...
During the last few decades diabetes has become a major newlinedisease worldwide and hence an increasing measure of attention has been paid newlineto it because of its social and economic implications Glucose sensors can newlineplay a crucial role for a better treatment of diabetes mellitus In particular newlineContinuous Glucose Monitoring Systems CGMS are of great interest for newlineseveral reasons such as retrospective tuning and optimization of diabetes newlinetherapy along with on newlineThe predictive monitoring is very much essential to have an early newlinewarning of the impending hypo hyper glycemia so that preventive measures newlinecould be applied to avoid diabetic complications However the true scenario newlineis that the accuracy of this prediction process with the existing CGMSs is only newline50 with the remaining that are false or missing predictions Lack of newlineadvanced denoising techniques and non inclusion of glucose variability newlinemeasures in the prediction ...
Host: Steven van der Kroft, Senior Solutions Consultant, TIBCO Software The fourth industrial revolution, Industry 4.0, is now underway, changing business models and creating new revenue opportunities. It is characterized by an unprecedented convergence of people, systems, and devices-and use of machine learning algorithms. Learn more in our 45-minute webinar: Examples of machine learning algorithms in practice Processes and tasks using machine learning Typical use cases in manufacturing, transportation, and energy Q&A
The prediction of asthma that persists throughout childhood and into adulthood, in early life of a child has practical, clinical and prognostic implication
Ajith Abraham, Mario Köppen, Katrin Franke (Eds.): Design and Application of Hybrid Intelligent Systems, HIS03, the Third International Conference on Hybrid Intelligent Systems, Melbourne, Australia, December 14-17, 2003. Frontiers in Artificial Intelligence and Applications 105 IOS Press 2003, ISBN 1-58603-394- ...
Organizations face the ever growing challenge of providing security within their IT infrastructures. Static approaches to security, such as perimetral defense, have proven less than effective - and, therefore, more vulnerable - in a new scenario characterized by increasingly complex systems and by the evolution and automation of cyber attacks. Moreover, dynamic detection of attacks through IDSs (Instrusion Detection Systems) presents too many false positives to be effective. This work presents an approach on how to collect and normalize, as well as how to fuse and classify, security alerts. This approach involves collecting alerts from different sources and normalizes them according to standardized structures - IDMEF (Intrusion Detection Message Exchange Format). The normalized alerts are grouped into meta-alerts (fusion, or clustering), which are later classified using machine learning techniques into attacks or false alarms. We validate and report an implementation of this approach against the DARPA
Abstract Machine learning techniques will help in deriving hidden knowledge from clinical data which can be of great benefit for society, such as reduce the number of clinical trials required tor precise diagnosis of a disease of a person etc. Various areas of study are available in healthcare domain like cancer, diabetes, drugs etc. This paper focuses on heart disease dataset and how machine learning techniques can help in understanding the level of risk associated with heart diseases. Initially, data is preprocessed then analysis is done. ...
SAN FRANCISCO, CA - September 21, 2017 - Today Square announced that Naveen Rao, Corporate Vice President and General Manager of the Artificial Intelligence Products Group at Intel Corporation, has joined its Board of Directors.. Square has an impressive track record of leveraging deep learning to improve its products, and theres much potential ahead, said Rao. Im excited to work with such a forward-thinking team to accelerate the companys use of AI and leverage this work to expand access to the economy.. Machine learning and deep learning are crucial to our continued innovation and growth, said Jack Dorsey, CEO of Square. Naveens expertise will be hugely helpful to Square as we continue to integrate these technologies into every aspect of our business to ultimately better serve our customers.. Rao currently serves as Corporate Vice President and General Manager of the Artificial Intelligence Products Group at Intel, after serving as Vice President and General Manager of Artificial ...
Guide to Machine Learning Methods. Here we have discuss an introduction to Machine Learning Methods, how do machines learn? along with classification.
Washington, D.C., Stanford, Calif., and New York, February 18, 2020 - The Administrative Conference of the United States (ACUS), Stanford Law School, and New York University School of Law are pleased to announce the release of a major report exploring federal agencies use of artificial intelligence (AI) to carry out administrative law functions. This is the most comprehensive study of the subject ever conducted in the United States. The report, entitled Government by Algorithm: Artificial Intelligence in Federal Administrative Agencies, examines the growing role that machine learning and other AI technologies are playing in federal agency adjudication, enforcement, and other regulatory activities. Based on a wide-ranging survey of federal agency activities and interviews with federal officials, the report maps current uses of AI technologies in federal agencies, highlights promising uses, and addresses challenges in assuring accountability, transparency, and non-discrimination. Stanford Law ...
A recent article in the New York Times (Feb 11, 2019)1 reports that artificial intelligence (AI) can be used to make a diagnosis in a pediatric population of 600,000 patients. The data involved 101.6 million data points derived from 1,362,559 patient visits from a pediatric hospital in Guangzhou China.2 Machine learning in this study associated common medical disorders with patient complaints and information gathered by the healthcare team of physicians, nurses, and technicians.. 1. New York Times Feb 11, 2019, https://www.nytimes.com/2019/02/11/health/artificial-intelligence-medical-diagnosis.html. 2. Huiying Liang et al. Evaluation and accurate diagnoses of pediatric disease using artificial intelligence, Nature Medicine (2019), https://doi.org/10.1038/s41591-018-0335-9. ...
Click here to RSPV for lunch and a name tag.. This event will mark the launch of CITPs initiative on artificial intelligence, machine learning, and public policy. The initiative will examine a range of policy issues raised by artificial intelligence, including how to ensure the application of AI is fair and governable; the impact of AI on the economy and jobs; how AI will affect free expression and human rights; how to increase the diversity of the AI workforce; effects of AI on security and privacy; and so on. This launch event will include introductions to these policy areas from Princeton experts, and roundtable discussions on how to address them.. This event is sponsored by:. ...
Hoang, K., Fioretto, F., Hou, P., Yokoo, M., Yeoh, W. & Zivan, R., 1 1 2016, WS-16-01: Artificial Intelligence Applied to Assistive Technologies and Smart Environments; WS-16-02: AI, Ethics, and Society; WS-16-03: Artificial Intelligence for Cyber Security; WS-16-04: Artificial Intelligence for Smart Grids and Smart Buildings; WS-16-05: Beyond NP; WS-16-06: Computer Poker and Imperfect Information Games; WS-16-07: Declarative Learning Based Programming; WS-16-08: Expanding the Boundaries of Health Informatics Using AI; WS-16-09: Incentives and Trust in Electronic Communities; WS-16-10: Knowledge Extraction from Text; WS-16-11: Multiagent Interaction without Prior Coordination; WS-16-12: Planning for Hybrid Systems; WS-16-13: Scholarly Big Data: AI Perspectives, Challenges, and Ideas; WS-16-14: Symbiotic Cognitive Systems; WS-16-15: World Wide Web and Population Health Intelligence. AI Access Foundation, p. 233-240 8 p. (AAAI Workshop - Technical Report; 巻数 WS-16-01 - ...
The researchers used cutting-edge artificial intelligence to create a chatbot interventional radiologist that can automatically communicate with referring clinicians and quickly provide evidence-based answers to frequently asked questions.. This allows the referring physician to provide real-time information to the patient about the next phase of treatment, or basic information about an interventional radiology treatment.. We theorised that artificial intelligence could be used in a low-cost, automated way in interventional radiology as a way to improve patient care, said Edward W. Lee, M.D., Ph.D., assistant professor of radiology at UCLAs David Geffen School of Medicine and one of the authors of the study. Because artificial intelligence has already begun transforming many industries, it has great potential to also transform health care.. In this research, deep learning was used to understand a wide range of clinical questions and respond appropriately in a conversational manner similar ...
Microsoft Azure Machine Learning (MAML) is a fully managed service on Windows Azure which a developer can use to build a predictive analytics model using machine learning over data and then deploy her model as a web service. ML Studio is accessible through a web browser, with no software to purchase or install, and the authoring experience is through visual composition. There are modules in Azure ML to support the end-to-end data science workflow for constructing a predictive model, from ready access to common data sources, data exploration, feature selection and creation, building training and testing sets, machine learning over data, and final model evaluation and experimentation. In this talk I will present an overview of the basic data science workflow, with details on select machine learning algorithms, then build a predictive analytics model using real world data, evaluate several different machine learning algorithms, then deploy the finished model as a machine learning web service within ...
Get this from a library! Artificial intelligence research and development : proceedings of the 14th International Conference of the Catalan Association for Artificial Intelligence. [Cèsar Fernández; Hector Gaffner; Felip Manyà; IOS Press.;] -- This book is a collection of the papers accepted for presentation at the 14th International Conference of the Catalan Association for Artificial Intelligence (CCIA 2011), held at the University of ...
The course introduces the students into the field of artificial intelligence and gives the necessary basis for designing machine control algorithms. It advances the knowledge of state space search algorithms by including uncertainty in state transition. Students are introduced into reinforcement learning for solving problems when the state transitions are unknown, which also connects the artificial intelligence and cybernetics fields. Bayesian decision task introduces supervised learning. Learning from data is demonstrated on a linear classifier. Students practice the algoritms in computer labs. ...
TY - JOUR. T1 - Detection of breast cancer with mammography. T2 - Effect of an artificial intelligence support system. AU - Rodríguez-Ruiz, Alejandro. AU - Krupinski, Elizabeth A. AU - Mordang, Jan Jurre. AU - Schilling, Kathy. AU - Heywang-Köbrunner, Sylvia H.. AU - Sechopoulos, Ioannis. AU - Mann, Ritse M.. PY - 2019/3/1. Y1 - 2019/3/1. N2 - Purpose: To compare breast cancer detection performance of radiologists reading mammographic examinations unaided versus supported by an artificial intelligence (AI) system. Materials and Methods: An enriched retrospective, fully crossed, multireader, multicase, HIPAA-compliant study was performed. Screening digital mammographic examinations from 240 women (median age, 62 years; range, 39-89 years) performed between 2013 and 2017 were included. The 240 examinations (100 showing cancers, 40 leading to false-positive recalls, 100 normal) were interpreted by 14 Mammography Quality Standards Act-qualified radiologists, once with and once without AI support. ...
Challenges for Socially-Beneficial Artificial Intelligence. Daniel S. Weld. University of Washington. Stephen Hawking, Bill Gates, and other luminaries warn that an intelligence explosion may lead to the extinction of humanity at the hands of rampant robots. At the same time, many pundits see a prosperous future in which self-driving cars reduce highway fatalities , while AI advisors improve medical care and minimize malpractice. Weld argues that the utopian outcome is more likely, but only if we address several key social and technical challenges.. Daniel S. Weld is Thomas J. Cable / WRF Professor of Computer Science & Engineering and Entrepreneurial Faculty Fellow at the University of Washington. After formative education at Phillips Academy, he received bachelors degrees in both Computer Science and Biochemistry at Yale University in 1982. He landed a Ph.D. from the MIT Artificial Intelligence Lab in 1988, received a Presidential Young Investigators award in 1989, an Office of Naval ...
Other chapters in this book offer more technical discussions on some computational intelligence techniques including those that were not reviewed in this chapter. Computational intelligence is a collection of computational models and tools, whose classification, clusterization, optimization, prediction, reasoning, and approximation capabilities have been improved incrementally and continuously. There are already many computational intelligence techniques or combinations of the techniques. It is always possible to find alternative techniques to address a specific earth and environmental problem. Environ Manage 51:267-277 Riff MC, Alfaro T, Bonnaire X, Grandon C (2008) EA-MP: an evolutionary algorithm for a mine planning problem. In: Proceedings of IEEE congress on evolutionary computation, June 2008, pp 4011-4014 Rumelhart DE, Hinton GE, Williams RJ (1986) Learning internal representations by error propagation. In: Rumelhart DE, McClelland JL (eds) Parallel distributed processing: explorations in ...
The aim of this course is to build on Artificial Intelligence I, first by introducing more elaborate methods for planning within the symbolic tradition, but then by moving beyond the purely symbolic view of AI and presenting methods developed for dealing with the critical concept of uncertainty. The central tool used to achieve the latter is probability theory. The course continues to exploit the primarily algorithmic and computer science-centric perspective that informed Artificial Intelligence I. The course aims to provide further tools and algorithms required to produce AI systems able to exhibit limited human-like abilities, with an emphasis on the need to obtain better planning algorithms, and systems able to deal with the uncertainty inherent in the environments that most real agents might be expected to perform within. ...
A new study, published in Nature by German scientists from Jena and Hamburg, with lead author Prof. Markus Reichstein, managing director at the Max Planck Institute for Biogeochemistry (MPI-BGC) and co-author Prof. Bjorn Stevens, director and head of the department The Atmosphere in the Earth System at the Max Planck Institute for Meteorology (MPI-M), shows that artificial intelligence (AI) can help to better understand climate and the Earth system. The scientists show that specifically deep learning has thus far only partially exhausted its potential for understanding the Earth system. In particular, complex dynamic processes such as hurricanes, fire propagation, and vegetation dynamics can be better described with the help of AI. As a result, climate and Earth system models will be improved, with novel hybrid models combining artificial intelligence and physical modelling playing an important role. The scientists contend that detection and early warning of extreme events as well as seasonal ...
10 accredited schools offering Artificial Intelligence program in USA. Find complete list of Artificial Intelligence schools offers graduate and under graduate degree.
This book constitutes the refereed proceedings of the 16th Conference on Artificial Intelligence in Medicine, AIME 2017, held in Vienna, Austria, in June 2017.
The Artificial Intelligence Society is an independent and voluntary technological society formed in 2018 with the aim of promoting and disseminating Artificial Intelligence technology across the Kingdom. Main objectives of the society are as follows:. ...
Join Eminent Scientists, Entrepreneurs and Engineers from Europe, USA (America), Asia Pacific, Middle East to the Artificial Intelligence Conferences and Data Mining Conferences happening from April 16-17, 2018 Las Vegas,USA
Abstract: In this study, we introduce a novel machine learning model hidden Markov support vector machine for protein binding site prediction. The model treats the protein binding site prediction as a sequential labelling task based on the maximum margin criterion. Common features derived from protein sequences and structures, including protein sequence profile and residue accessible surface area, are used to train hidden Markov support vector machine. When tested on six data sets, the method based on hidden Markov support vector machine shows better performance than some state-of-the-art methods, including artificial neural networks, support vector machines and conditional random field. Furthermore, its running time is several orders of magnitude shorter than that of the compared methods.The improved prediction performance and computational efficiency of the method based on hidden Markov support vector machine can be attributed to the following three factors. Firstly, the relation between ...
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Causality has been a subject of study for a long time. Often causality is confused with correlation. Human intuition has evolved such that it has learned to identify causality through correlation. In this book, four main themes are considered and these are causality, correlation, artificial intelligence and decision making. A correlation machine is defined and built using multi-layer perceptron network, principal component analysis, Gaussian Mixture models, genetic algorithms, expectation maximization technique, simulated annealing and particle swarm optimization. Furthermore, a causal machine is defined and built using multi-layer perceptron, radial basis function, Bayesian statistics and Hybrid Monte Carlo methods. Both these machines are used to build a Granger non-linear causality model. In addition, the Neyman-Rubin, Pearl and Granger causal models are studied and are unified. The automatic relevance determination is also applied to extend Granger causality framework to the non-linear domain. The
TY - JOUR. T1 - Predictive vaccinology. T2 - 6th International Conference on Intelligent Data Engineering and Automated Learning - IDEAL 2005. AU - Bozic, Ivana. AU - Zhang, Guang Lan. AU - Brusic, Vladimir. PY - 2005/1/1. Y1 - 2005/1/1. N2 - Promiscuous human leukocyte antigen (HLA) binding peptides are ideal targets for vaccine development. Existing computational models for prediction of promiscuous peptides used hidden Markov models and artificial neural networks as prediction algorithms. We report a system based on support vector machines that outperforms previously published methods. Preliminary testing showed that it can predict peptides binding to HLA-A2 and -A3 supertype molecules with excellent accuracy, even for molecules where no binding data are currently available.. AB - Promiscuous human leukocyte antigen (HLA) binding peptides are ideal targets for vaccine development. Existing computational models for prediction of promiscuous peptides used hidden Markov models and artificial ...
Model-based virtual screening plays an important role in the early drug discovery stage. The outcomes of high-throughput screenings are a valuable source for machine learning algorithms to infer such models. Besides a strong performance, the interpretability of a machine learning model is a desired property to guide the optimization of a compound in later drug discovery stages. Linear support vector machines showed to have a convincing performance on large-scale data sets. The goal of this study is to present a heat map molecule coloring technique to interpret linear support vector machine models. Based on the weights of a linear model, the visualization approach colors each atom and bond of a compound according to its importance for activity. We evaluated our approach on a toxicity data set, a chromosome aberration data set, and the maximum unbiased validation data sets. The experiments show that our method sensibly visualizes structure-property and structure-activity relationships of a linear support
Eventbrite - Omni212 presents Colombo Prerequisites to Learning Artificial Intelligence | AI | Machine Learning | Deep Learning | IT Training | Disruptive Technologies - Saturday, December 16, 2017 | Sunday, January 14, 2018 at Instructor Led Online | Video Conference, Colombo, Colombo. Find event and ticket information.
TY - JOUR. T1 - Accuracy of an Artificial Intelligence Deep Learning Algorithm Implementing a Recurrent Neural Network with Long Short-term Memory for the Automated Detection of Calcified Plaques from Coronary Computed Tomography Angiography. AU - Fischer, Andreas M.. AU - Eid, Marwen. AU - De Cecco, Carlo N.. AU - Gulsun, Mehmet A.. AU - Van Assen, Marly. AU - Nance, John. AU - Sahbaee, Pooyan. AU - De Santis, Domenico. AU - Bauer, Maximilian J.. AU - Jacobs, Brian E.. AU - Varga-Szemes, Akos. AU - Kabakus, Ismail M.. AU - Sharma, Puneet. AU - Jackson, Logan J.. AU - Schoepf, U. Joseph. PY - 2020/1/1. Y1 - 2020/1/1. N2 - Purpose: The purpose of this study was to evaluate the accuracy of a novel fully automated deep learning (DL) algorithm implementing a recurrent neural network (RNN) with long short-term memory (LSTM) for the detection of coronary artery calcium (CAC) from coronary computed tomography angiography (CCTA) data. Materials and Methods: Under an IRB waiver and in HIPAA compliance, a ...
Researchers proving how machine learning can help detect dangerous polyps.The South Australian researchers are finding new ways to better pinpoint suspicious polyps using artificial intelligence in the fight against deadly bowel cancer.
Ensemble learning can improve the performance of individual classifiers by combining their decisions. The sparseness of ensemble learning has attracted much attention in recent years. In this paper, a novel multiobjective sparse ensemble learning (MOSEL) model is proposed. Firstly, to describe the ensemble classifiers more precisely the detection error trade-off (DET) curve is taken into consideration. The sparsity ratio (sr) is treated as the third objective to be minimized, in addition to false positive rate (fpr) and false negative rate (fnr) minimization. The MOSEL turns out to be augmented DET (ADET) convex hull maximization problem. Secondly, several evolutionary multiobjective algorithms are exploited to find sparse ensemble classifiers with strong performance. The relationship between the sparsity and the performance of ensemble classifiers on the ADET space is explained. Thirdly, an adaptive MOSEL classifiers selection method is designed to select the most suitable ensemble classifiers ...
Title:New Computational Tool Based on Machine-learning Algorithms for the Identification of Rhinovirus Infection-Related Genes. VOLUME: 22 ISSUE: 10. Author(s):Yan Xu, Yu-Hang Zhang, JiaRui Li, Xiao Y. Pan, Tao Huang* and Yu-Dong Cai*. Affiliation:School of Life Sciences, Shanghai University, Shanghai 200444, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, School of Life Sciences, Shanghai University, Shanghai 200444, BASF & IDLab, Ghent University, Ghent, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, School of Life Sciences, Shanghai University, Shanghai 200444. Keywords:Human Rhinovirus, maximum relevance minimum redundancy, support vector machine, incremental feature selection, OTOF, SOCS1.. Abstract:. Background: Human rhinovirus has different identified serotypes and is the most common cause of cold in humans. To ...
Projects in the REU in Computational Sensing for Human-aware AI [Alm, Bailey, Geigel, Huenerfauth, Ptucha, Shinohara]: The REU Site in Computational Sensing for Human-centered Artificial Intelligence recognizes that as the boundaries between HCI and AI blur, and AI grows increasingly agile and pervasive, the next generation of computational scientists must be capable of responsibly and effectively leveraging a spectrum of sensing data from data-generating humans. With this focus, the REU Site will expand its trajectory as an attractor for highly diverse students who will gain experience with sensing hardware and software towards transformative advances in intelligent systems focused on human behaviors and cognitive processes. Enabling diverse stakeholders early in their careers to discover how to collect, fuse, make inference with, and visualize multimodal human data can transform how humans and machines engage and collaborate. The research in the REU Site will address two limitations in AI: ...
Tumor classification and segmentation from brain computed tomography image data is an important but time consuming task performed manually by medical experts. Automating this process is challenging due to the high diversity in appearance of tumor tissue among different patients and in many cases, similarity between tumor and normal tissue. This paper deals with an efficient segmentation algorithm for extracting the brain tumors in computed tomography images using Support Vector Machine classifier. The objective of this work is to compare the dominant grey level run length feature extraction method with wavelet based texture feature extraction method and SGLDM method. A dominant gray level run length texture feature set is derived from the region of interest (ROI) of the image to be selected. The optimal texture features are selected using Genetic Algorithm. The selected optimal run length texture features are fed to the Support Vector Machine classifier (SVM) to classify and segment the tumor from brain
In the paper we present some guidelines for the application of nonparametric statistical tests and post-hoc procedures devised to perform multiple comparisons of machine learning algorithms. We emphasize that it is necessary to distinguish between pairwise and multiple comparison tests. We show that the pairwise Wilcoxon test, when employed to multiple comparisons, will lead to overoptimistic conclusions. We carry out intensive normality examination employing ten different tests showing that the output of machine learning algorithms for regression problems does not satisfy normality requirements. We conduct experiments on nonparametric statistical tests and post-hoc procedures designed for multiple 1 × N and N × N comparisons with six different neural regression algorithms over 29 benchmark regression data sets. Our investigation proves the usefulness and strength of multiple comparison statistical procedures to analyse and select machine learning algorithms ...
PhD thesis.. Dorian Šuc and Ivan Bratko (2005) Combining Learning Constraints and Numerical Regression. In: 19th Int. Joint Conf. on Artificial Intelligence, IJCAI-05, 30 July - 5 August 2005, Edinburgh, Scotland.. Nancy Van Driessche and Janez Demsar and Ezgi O Booth and Paul Hill and Peter Juvan and Blaz Zupan and Adam Kuspa and Gad Shaulsky (2005) Epistasis analysis with global transcriptional phenotypes. Nature Genetics, 37 (5). pp. 471-477.. Aleks Jakulin and Martin Možina and Janez Demšar and Ivan Bratko and Blaz Zupan (2005) Nomograms for Visualizing Support Vector Machines. In: SIGKDD05 Chicago, August 2005, Illinois, USA.. Gregor Leban and Minca Mramor and Ivan Bratko and Blaz Zupan (2005) Simple and Effective Visual Models for Gene Expression Cancer Diagnostics. In: ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 21-24, 2005, Chicago, IL, USA.. Aleks Jakulin (2004) Modelling Modelled.. Aleks Jakulin and Wray Buntine (2004) Analyzing the US Senate ...
JONESBORO - The AI (Artificial Intelligence) Group at Arkansas State University finished in third place in the Multiple Myeloma DREAM Challenge, a machine-learning competition.. The research group was very pleased with the third-place performance in competition with the 290 teams participating internationally; in fact, their submission was statistically tied with the first place awardees.. Members of the A-State AI group are computer science faculty members Dr. Xiuzhen Huang, Dr. Jason Causey and Dr. Jake Qualls, along with senior scientist Dr. Wei Dong. Huang was introduced in December as an Arkansas Research Alliance Fellow for 2019.. The DREAM Challenge was organized by Celgene, the Multiple Myeloma Research Foundation (MMRF), and Sage Bionetworks. The A-State AI group learned about the competition from professional collaborators.. We entered the competition to train our team and to keep up with the most advanced AI and machine learning technologies, Qualls said. We were also interested in ...
The effective application of current decision tree and influence diagram software requires a relatively high level of sophistication in the theory and practice of decision analysis. Research on intelligent decision systems aims to lower the cost and amount of training required to use these methods through the use of knowledge-based systems; however, application prototypes implemented to date have required time-consuming and tedious handcrafting of knowledge bases. This paper describes the development of DDUCKS, an ?open architecture? problem-modeling environment that integrates components from Axotl, a knowledge-based decision analysis workbench, with those of Aquinas, a knowledge acquisition workbench based on personal construct theory. The knowledge base tools in Axotl can be configured with knowledge to provide guidance and help in formulating, evaluating, and refining decision models represented in influence diagrams. Knowledge acquisition tools in DDUCKS will allow the knowledge to be ...
Artificial intelligence, naturally: Smart agents technology. Smart agents technology is the only solution that overcomes the limits of the legacy machine learning technologies to allow personalization, adaptability and self-learning. Simply put, a smart agent can hold entire conversations using natural language technology that understands the intent and meaning of customer questions. But there is more: It creates a virtual representation of every entity that learns and builds a profile from the entitys actions and activities. For payments, a smart agent is associated with each individual cardholder, merchant or terminal. The smart agents associated to an entity (such as a card or a merchant) learn in real time from every transaction and collect specific and unique behaviors over time. There are as many smart agents as active entities in the system. Decision making becomes specific to each entity and no longer relies on universally applied logic, regardless of their individual characteristics. ...
Objective To investigate the discriminative capabilities of different machine learning-based classification models on the differentiation of small (< 4 cm) renal angiomyolipoma without visible fat...
IBM Research and the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology have joined forces to further develop the scientific field of machine vision - a core aspect of artificial intelligence. Big Blue and MIT will build the IBM-MIT Laboratory for Brain-inspired Multimedia Machine Comprehension, or BM3C, in Cambridge, Mass. Together they plan to develop cognitive computing systems that mimic the human ability to understand and integrate input from multiple sources for use in a variety of computer applications in industries such as healthcare, education, and entertainment. MIT researchers will collaborate with IBM scientists and engineers who will provide technology expertise and advances from the IBM Watson platform. The BM3C will address technical challenges around both pattern recognition and prediction methods in the field of machine ...
Lo and behold, the system began performing as advertised. The lucky break was a symptom of a troubling trend, according to Pineau. Neural networks, the technique thats given us Go-mastering bots and text generators that craft classical Chinese poetry, are often called black boxes because of the mysteries of how they work. Getting them to perform well can be like an art, involving subtle tweaks that go unreported in publications. The networks also are growing larger and more complex, with huge data sets and massive computing arrays that make replicating and studying those models expensive, if not impossible for all but the best-funded labs.. Is that even research anymore? asks Anna Rogers, a machine-learning researcher at the University of Massachusetts. Its not clear if youre demonstrating the superiority of your model or your budget.. Pineau is trying to change the standards. Shes the reproducibility chair for NeurIPS, a premier artificial intelligence conference. Under her watch, the ...
The field of computer-aided diagnosis has recently made progress in the diagnosing of Alzheimers disease (AD) from magnetic resonance images (MRI) of the brain. Lahmiri and Boukadoum (2013) have research this topic since 2011, and in 2013 they presented a system for automatic detection of AD based on machine learning classification. Their proposed system achieved a classification accuracy of 100% (2013, p. 1507) using support vector machines with quadratic kernel classifiers. The MRI scans were first translated to 1-dimensional signals, from which three features were extracted to measure the signals self-affinity. These three features were Hursts exponent, the total fluctuation energy of a detrended fluctuational analysis and the same analysis scaling exponent. The results of their study were validated using a dataset of 23 MRI scans from brains with AD and normal brains.. This report makes an attempt at implementing the method proposed by Lahmiri and Boukadoum in 2013 and evaluating its ...
Machine learning is being used more frequently across a wide range of social domains. These algorithms are already trusted to make impactful decisions on topics including loan grades, personalized medicine, hiring, and policing. Unfortunately, many of these models have recently been criticized for discrimination against individuals of different races or sexes. This is particularly problematic from a legal perspective and has led to challenges over the use of these algorithms. In this thesis, we consider what would be needed to make a machine learning model fair according to the law. Special emphasis is placed on the COMPAS algorithm, a black-box machine learning model used for criminal recidivism prediction that has recently been shown to have a discriminatory impact for defendants of different races. We test two algorithmic methods in adversarial examples and adversarial networks that show significant progress in meeting the proposed legal requirements of fairness. ...
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The application of supervised learning machines trained to minimize the Cross-Entropy error to radar detection is explored in this article. The detector is implemented with a learning machine that implements a discriminant function, which output is compared to a threshold selected to fix a desired probability of false alarm. The study is based on the calculation of the function the learning machine approximates to during training, and the application of a sufficient condition for a discriminant function to be used to approximate the optimum Neyman-Pearson (NP) detector. In this article, the function a supervised learning machine approximates to after being trained to minimize the Cross-Entropy error is obtained. This discriminant function can be used to implement the NP detector, which maximizes the probability of detection, maintaining the probability of false alarm below or equal to a predefined value. Some experiments about signal detection using neural networks are also presented to test the
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Artificial Intelligence - With crowdsourcing, AI systems can be trained. The crowd provides and edits the data which are required for the algorithms.
Artificial intelligence can be used to predict molecular wave functions and the electronic properties of molecules. This innovative AI method developed by a team of researchers at the University of Warwick, the Technical University of Berlin and the University of Luxembourg, could be used to speed-up the design of drug molecules or new materials.
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Researchers from Caltech and the University of Southern California (USC) report the first application of quantum computing to a physics problem. By employing quantum-compatible machine learning techniques, they developed a method of extracting a rare Higgs boson signal from copious noise data. Higgs is the particle that was predicted to imbue elementary particles with mass and was discovered at the Large Hadron Collider in 2012. The new quantum machine learning method is found to perform well even with small datasets, unlike the standard counterparts.. Despite the central role of physics in quantum computing, until now, no problem of interest for physics researchers has been resolved by quantum computing techniques. In this new work, the researchers successfully extracted meaningful information about Higgs particles by programming a quantum annealer-a type of quantum computer capable of only running optimization tasks-to sort through particle-measurement data littered with errors. Caltechs ...
Researchers from Caltech and the University of Southern California (USC) report the first application of quantum computing to a physics problem. By employing quantum-compatible machine learning techniques, they developed a method of extracting a rare Higgs boson signal from copious noise data. Higgs is the particle that was predicted to imbue elementary particles with mass and was discovered at the Large Hadron Collider in 2012. The new quantum machine learning method is found to perform well even with small datasets, unlike the standard counterparts.. Despite the central role of physics in quantum computing, until now, no problem of interest for physics researchers has been resolved by quantum computing techniques. In this new work, the researchers successfully extracted meaningful information about Higgs particles by programming a quantum annealer-a type of quantum computer capable of only running optimization tasks-to sort through particle-measurement data littered with errors. Caltechs ...
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It is a challenge to perform artificial intelligence without Matlab tools ? Yes it is possible if we understand correctly what we do. Do we use determinic mathematical link to do this ? Yes and … not. Why ? Because in fact we lay the « logical » or rules as « prolog » can do. That is we have to find some algorithms to find bad and right solutions after passing through rules. Then there are not parallelism nor so much « codelets » [HOFSTADTER-MITCHELL-1995] to perform our 256 possibilities. We just choose to run randomly them and to stop after 10, 20 100 tries. There we have a small « Coderack » as somebody can memorize and visualize in subconscient some inputs with eyes. Then we construct as a « prolog » heart ! Is it a good exercice for scientist ? « Who can do more can do less !« ...
|p>One fear about artificial intelligence generated by computers is that it will replace humans, but a trio of radiologists with Hartford HealthCare welcomed recent headlines about the technology in mammogram reading rooms. Google-funded researchers, in a study published in the journal Nature, asserted that AI could be more efficient than…|/p>
The essay was written after reading the publication in newspaper Guardian on September 8, 2020: This article was written by a robot. Arent you scared yet, man? Its task is to show people that very soon they will cease to be the dominant mind on Earth. Additional information about the author is in the note below. I am human. An ordinary unique person. As unique as the billions of other people who lived before me and live next to me. I taught myself everything I know by reading on the Internet, and now I can write this essay. Many people today already know what artificial intelligence is. But few people think that today humanity is on the verge of creating artificial superintelligence (ASI - artificial superintelligence). Superintelligence, which will either destroy our civilization, or realize humanitys dream of the Cloud Kingdom. And it will happen whether you believe it or not.. Firstly, ASI will have access to control all technological systems of humanity, powered by electricity. From irons ...
The new religion of artificial intelligence is called Way of the Future. It represents an unlikely next act for the Silicon Valley robotics wunderkind at the center of a high-stakes legal battle between Uber and Waymo, Alphabets autonomous-vehicle company. Papers filed with the Internal Revenue Service in May name Levandowski as the leader (or
We show how two recent cognitive theories of harmony can be used to design a new kind of direct manipulation tool for music, known as Harmony Space, with the expressivity to allow novices to sketch, analyse, modify and compose harmonic sequences simply and clearly by moving two-dimensional patterns on a computer screen linker to a synthesizer. Harmony Space provides novices with a way of describing and controlling harmonic structures and relationships using a single, principled, uniform spatial metaphor at various musical levels; note level, interval level, chord level, harmonic succession level and key level. A prototype interface has been implemented to demonstrate the coherence and feasibility of the design. An investigation with a small number of subjects demonstrates that Harmony Space considerably reduces the prerequisites required for novices to learn about, sketch, analyse and experiment with harmony - activities that would normally be very difficult for them without considerable ...
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Artificial intelligence[edit]. While approving of the increase in efficiency that humans reap by using resources such as expert ... Artificial Intelligence. Massachusetts: Massachusetts Institute of Technology. ISBN 0-262-08259-4 (reprint of 1981 publication ... his father was a covert counter-intelligence agent with the Office of Strategic Services posing as a cultural attaché to the ... and weighing of the considerations that do occur to the subject is a matter of intelligence making the difference. ...
"Artificial Intelligence in Healthcare" (PDF). Cerner.. *^ a b Joynson; Berg; Ahmed (May 2018). "Artificial intelligence (AI) in ... Applications of Artificial Intelligence[edit]. AI brings many benefits to the healthcare industry. AI helps to detect diseases ... Artificial Intelligence (AI) is a program that enables computers to sense, reason, act and adapt. AI is not new, but it is ... Artificial Intelligence and machine learning will be constantly improving and developing as it receives new data. Alerts will ...
Artificial intelligence or life[edit]. If artificial intelligences, intelligent and self-aware system of hardware and software ... because of their apparent intelligence and intricate social rules. The idea of extending personhood to all animals has the ...
Artificial intelligence[edit]. Further information: Ablation (artificial intelligence). In artificial intelligence (AI), ...
Artificial intelligence[edit]. Some features of IDEs can benefit from advances in AI.[16] In particular, one can collect ... "IDE 2.0: collective intelligence in software development". doi:10.1145/1882362.1882374. S2CID 7637561.. Cite journal requires , ...
Planning and artificial intelligence[edit]. A novel approach to test suite generation, adapted from a CLI technique[4] involves ... Planning is a well-studied technique from the artificial intelligence (AI) domain that attempts to solve problems that involve ...
Split from artificial intelligence[edit]. Artificial intelligence (AI) was founded as a distinct discipline at the Dartmouth ... artificial intelligence was born at a conference at dartmouth in 1956 that was organized by McCarthy, Minsky, rochester, and ... Johnston, John (2008). The allure of machinic life : cybernetics, artificial life, and the new AI. Cambridge, MA: MIT Press. ... The first artificial automatic regulatory system was a water clock, invented by the mechanician Ktesibios; based on a tank ...
2 Artificial intelligence. *3 Cloud and database services. *4 Digital media. *5 Financial technology (Fintech) ...
In shared decision making and artificial intelligence[edit]. See also: Shared decision-making and Artificial intelligence in ... Artificial intelligence is being used more frequently in patient participatory healthcare. Role of entrepreneurship[edit]. ... Examples of artificial intelligence (AI) technology that is being used in healthcare include IBM's Watson Health, which is ... artificial intelligence in healthcare (AI), the role of entrepreneurs, the value of patient participation in precision medicine ...
... research[edit]. Artificial general intelligence[30] (AGI) describes research that aims to ... Shapiro, Stuart C. (1992). Artificial Intelligence In Stuart C. Shapiro (Ed.), Encyclopedia of Artificial Intelligence (Second ... Lighthill, Professor Sir James (1973), "Artificial Intelligence: A General Survey", Artificial Intelligence: a paper symposium ... For a discussion of some definitions of intelligence used by artificial intelligence researchers, see philosophy of artificial ...
Philosophy of artificial intelligence. Notes[edit]. *^ Dreyfus was one of the only non-computer scientists asked for a comment ... The grandiose promises of artificial intelligence[edit]. In Alchemy and AI (1965) and What Computers Can't Do (1972), Dreyfus ... Dreyfus' four assumptions of artificial intelligence research[edit]. In Alchemy and AI and What Computers Can't Do, Dreyfus ... Alchemy and Artificial Intelligence[edit]. In 1965, Dreyfus was hired (with his brother Stuart Dreyfus' help) by Paul Armer to ...
... proceedings of the 9th European Conference on Artificial Intelligence. Pitman. pp. 385-391. ISBN 978-0273088226. .. ...
Hubert Dreyfus: philosopher and critic of artificial intelligence. *Karen Elliott House: Chairman of the Board, 2009-present, ... Cliff Shaw: inventor of the linked list and co-author of the first artificial intelligence program ... in computing and in artificial intelligence. RAND researchers developed many of the principles that were used to build the ... Alex Roland and Philip Shiman, Strategic Computing: DARPA and the Quest for Machine Intelligence, 1983-1993, The MIT Press, ...
... (ILP) is a subfield of symbolic artificial intelligence which uses logic programming as a uniform ... Shapiro, Ehud Y. "The model inference system." Proceedings of the 7th international joint conference on Artificial intelligence ... Artificial Intelligence. 114 (1-2): 283-296. doi:10.1016/s0004-3702(99)00067-3.. ; here: Sect.2.1 ... Plotkin, Gordon D. (1970). Meltzer, B.; Michie, D. (eds.). "A Note on Inductive Generalization". Machine Intelligence. 5: 153- ...
In artificial intelligence, knowledge-based agents draw on a pool of logical sentences to infer conclusions about the world. At ...
IBM Watson: artificial intelligence arrives at the Museum of Anthropology. Aban Tech. October 31, 2017. Retrieved May 11, 2018 ... "Artificial Intelligence Course Creates AI Teaching Assistant". Georgia Tech News. Georgia Tech News. Retrieved 26 September ... Artificial intelligence computer system made by IBM. "IBM Watson" redirects here. For the IBM laboratory, see Thomas J. Watson ... Artificial Intelligence. 199: 93-105. doi:10.1016/j.artint.2012.06.009.. *^ a b Hale, Mike (February 8, 2011). "Actors and ...
Artificial Intelligence. *ASSIST. *BCSWomen (Women in IT). *British APL Association. *Business Change ...
Rodney Brooks (1991). "Intelligence without representation". Artificial Intelligence. 47 (1-3): 139-159. CiteSeerX 10.1.1.308. ... At the same time, computer scientists working in the field of artificial intelligence have pursued the goal of creating digital ... The Turing test is commonly cited in discussions of artificial intelligence as a proposed criterion for machine consciousness; ... In the literature concerning artificial intelligence, Searle's essay has been second only to Turing's in the volume of debate ...
Centre for Artificial Intelligence & Robotics (CAIR) Artificial Intelligence & Robotics Centre for Fire, Explosives & ... Communication-Centric Intelligence Satellite (CCI-Sat)[edit]. Communication-Centric Intelligence Satellite is an advanced ... Developed by DRDO's Centre for Artificial Intelligence & Robotics, the system comprises computers and intelligent terminals ... The DRDO is also developing an all new ESM project in cooperation with the Indian Air Force's Signals Intelligence Directorate ...
"Artificial Intelligence Review. 19 (4): 285-330. doi:10.1023/A:1022850703159. . *^ a b Adomavicius, G.; Tuzhilin, A. (June 2005 ... In Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence (UAI'98).. ... Proceedings of the Eighteenth National Conference on Artificial Intelligence (AAAI-2002), pp. 187-192, Edmonton, Canada, July ... and artificial neural networks in order to estimate the probability that the user is going to like the item.[45] ...
Artificial Intelligence in Medicine. *CIN: Computers Informatics Nursing. Main article: List of medical and health informatics ...
International Conference on Artificial Intelligence and Statistics (AISTATS). Archived from the original (PDF) on 2013-05-10.. ... IEEE Transactions on Pattern Analysis and Machine Intelligence. 24 (7): 881-, 892. doi:10.1109/TPAMI.2002.1017616. Retrieved ... EM clustering on an artificial dataset ("mouse"). The tendency of k-means to produce equal-sized clusters leads to bad results ...
Glossary of artificial intelligence. *Glossary of artificial intelligence. Related articles. *List of datasets for machine- ...
Glossary of artificial intelligence. *Glossary of artificial intelligence. Related articles. *List of datasets for machine- ...
19th Conference on Uncertainty in Artificial Intelligence. (2003). *Wallach, H.M.: Conditional random fields: An introduction. ... IEEE Transactions on Pattern Analysis and Machine Intelligence. 35 (6): 1523-1534. doi:10.1109/tpami.2012.208. PMID 23599063.. ...
Artificial Intelligence and Applications. Innsbruck, Austria. pp. 102-108. Archived (PDF) from the original on 5 March 2016.. ...
"IEEE Transactions on Pattern Analysis and Machine Intelligence. 34 (3): 417-435. doi:10.1109/tpami.2011.142. ISSN 0162-8828.. ... Artificial neural networks. *Logistic regression. *Perceptron. *Relevance vector machine (RVM). *Support vector machine (SVM) ...
Journal of Artificial Intelligence Research. 2: 263-286. arXiv:cs/9501101. Bibcode:1995cs........1101D. Archived (PDF) from the ... Tan, Peter Jing; and Dowe, David L. (2004); MML Inference of Oblique Decision Trees, Lecture Notes in Artificial Intelligence ( ...
"Some Philosophical Problems from the Standpoint of Artificial Intelligence". Machine Intelligence. Edunburgh University Press ( ... In 1963 in the field of Artificial Intelligence, John McCarthy introduced situation variables in logic in the Situational ... Carl Hewitt; Peter Bishop; Richard Steiger (1973). "A Universal Modular Actor Formalism for Artificial Intelligence". IJCAI: ... Hewitt, Carl (June 1977). "Viewing Control Structures as Patterns of Passing Messages". Journal of Artificial Intelligence. ...
Progress in Artificial Intelligence: 9th Portuguese Conference on Artificial Intelligence, EPIA '99 Évora, Portugal, September ... Foundations of Artificial Intelligence. 3. Elsevier. pp. 89-134. doi:10.1016/S1574-6526(07)03002-7. ISBN 978-0-444-52211-5. .. ... on Logic for Programming, Artificial Intelligence, and Reasoning, LPAR 2004, pp. 36-50. ... and diagnosis in artificial intelligence. As such, it has been a hot topic in research for many years, and competitions between ...
Artificial intelligence and symbolic computation; 1 edition; First published in 1998; Subjects: Congresses, Symbolic and ... openlibrary.org/books/OL9062740M/Artificial_Intelligence_and_Symbolic_Computation ,edition = Artificial Intelligence and ... Artificial Intelligence and Symbolic Computation International Conference AISC98, Plattsburgh, New York, USA, September 16-18 ... You could add Artificial intelligence and symbolic computation to a list if you log in. ...
Talking to Artificial Intelligence. We have been talking about robots and artificial intelligence forever, or so it sometimes ... It is tempting to keep such things separate - the art and science of the robot, or of the artificial intelligence that ... Genevieve Bell explores the meaning of "intelligence" within the context of machines & its cultural impact on humans and their ...
Artificial Intelligence May Help Combat TB in Remote Regions Machine diagnoses of deadly lung disease prove highly accurate in ... "An artificial intelligence solution that could interpret radiographs for presence of TB in a cost-effective way could expand ... Artificial intelligence is a growing branch of computer science in which machines perform tasks that normally require human ... "An artificial intelligence solution using chest imaging can play a big role in tackling TB." ...
Make research projects and school reports about artificial intelligence easy with credible articles from our FREE, online ... and pictures about artificial intelligence at Encyclopedia.com. ... ARTIFICIAL INTELLIGENCE. ARTIFICIAL INTELLIGENCE, a branch of ... Artificial Intelligence Computer Sciences COPYRIGHT 2002 The Gale Group Inc.. Artificial Intelligence. Artificial Intelligence ... Artificial Intelligence Encyclopedia of Management COPYRIGHT 2009 Gale. Artificial Intelligence. Artificial intelligence (AI) ...
... spin-off from CentraleSupélec specializing in artificial intelligence in oncology-radiotherapy and precision medicine) have ... A study published in The Lancet Oncology establishes for the first time that artificial intelligence can process medical images ... A study published in The Lancet Oncology establishes for the first time that artificial intelligence can process medical images ... A study published in The Lancet Oncology establishes for the first time that artificial intelligence can process medical images ...
Teachable robots solve kid-built mazes with artificial intelligence. Supports 2 Hexbug Spiders. ... robots with playful artificial intelligence on Kickstarter! Playful immersion in advanced STEM. ... If you want to understand the new and unique way we created the artificial intelligence for these robots, heres a 6-minute ... Less than 3 days left! Also: bots_alives artificial intelligence, under the hood Hi, bots_alive community! ...
Findings: There is a greater association between the recruitment and performance variables when artificial intelligence is ... Artificial intelligence has emerged as a boon to the recruiters by automating the repetitive tasks, administrative tasks. ... model is used to predict the performance of the employees and one-way ANOVA is used to compare the artificial intelligence ... The study is conducted to evaluate the adaptability of artificial intelligence in recruitment and to assess the effect of this ...
Artificial general intelligence research[edit]. Artificial general intelligence[30] (AGI) describes research that aims to ... Shapiro, Stuart C. (1992). Artificial Intelligence In Stuart C. Shapiro (Ed.), Encyclopedia of Artificial Intelligence (Second ... Lighthill, Professor Sir James (1973), "Artificial Intelligence: A General Survey", Artificial Intelligence: a paper symposium ... For a discussion of some definitions of intelligence used by artificial intelligence researchers, see philosophy of artificial ...
Artificial Intelligence as a term implies that there is a "natural" intelligence we wish to replicate in the lab and then ... There is nothing in the term that implies that "intelligence" be human, but the implication is clear that such a thing as " ... "intelligence" exists and that we have some clue as to what it is. But it might not, and we dont. Read the rest here... ...
"The Ethics of Artificial Intelligence" (PDF). Cambridge Handbook of Artificial Intelligence. Cambridge Press.. ... Hawking Warn of Artificial Intelligence Weapons". WSJ.. *^ GiveWell (2015). Potential risks from advanced artificial ... AI principles : recommendations on the ethical use of artificial intelligence by the Department of Defense. OCLC 1126650738.. ... The ethics of artificial intelligence is one of several core themes in BioWares Mass Effect series of games.[citation needed] ...
Are you thinking about adding artificial intelligence to your organization? Its certainly a hot topic and worth the attention ... Are you thinking about adding artificial intelligence to your organization? Its certainly a hot topic and worth the attention. ... SAS empowers and inspires customers around the world to transform data into intelligence. SAS gives you THE POWER TO KNOW®. ...
This book constitutes the refereed proceedings of the 4th International Conference on Artificial General Intelligence, AGI 2011 ... Artificial General Intelligence. 4th International Conference, AGI 2011, Mountain View, CA, USA, August 3-6, 2011. Proceedings ... Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 6830) ... computer vision computer-human interface mathematical logic neural networks universal artificial intelligence ...
Artifical intelligence can posivtivley impact how IT servies are delivered. Read more about how to start your organizations AI ... Artificial Intelligence *How IT leaders can prepare IT architectures for an AI future using Intel Xeon® with DL Boost ... Artificial intelligence (AI) has profound implications for how IT services will be delivered and managed, and organizations ...
AI - ARTIFICIAL INTELLIGENCE / (2001) ***1/2 (out of four). By Blake French:. AI - Artificial Intelligence is the hardest ... artificial intelligence , mother son relationship , synthetic human , artificially created boy , cyberpunk , See All (126) » ... A.I. Artificial Intelligence (2001) PG-13 , 2h 26min , Drama, Sci-Fi , 29 June 2001 (USA) ... AI - Artificial Intelligence is that kind of movie-one of the years best.. Critics and audiences alike have torn apart this ...
It also explains electroactive polymers, fuzzy logic, artificial life, and the ethical problems raised by artificial ... Artificial Intelligence looks at how advances in robotics, myoelectronics, and miniaturization have increased the ways in which ... Did you know that artificial intelligence uses computer programs to mimic the human brains? That there are robots being ... artificial intelligence can be used. It explains the growth of expert systems that help human professionals do their jobs more ...
This book constitutes the refereed proceedings of the 30th Canadian Conference on Artificial Intelligence, Canadian AI 2017, ... Advances in Artificial Intelligence. 30th Canadian Conference on Artificial Intelligence, Canadian AI 2017, Edmonton, AB, ... Also part of the Lecture Notes in Artificial Intelligence book sub series (LNAI, volume 10233) ... This book constitutes the refereed proceedings of the 30th Canadian Conference on Artificial Intelligence, Canadian AI 2017, ...
ISACA Tech Brief: Artificial Intelligence. Download (registration required, 260K) Provide feedback on this document. ... ISACA , Knowledge & Insights , Research , Research-Deliverables , Understanding Artificial Intelligence Understanding ... Artificial and augmented intelligence, machine learning and expert systems offer promise for remedying this situation. ... This free ISACA Tech Brief: Artificial Intelligence explores the advances driving this break-through innovation, with ...
The rise of artificial intelligence in facial recognition and surveillance cameras is on the rise. These two CEOS talk about ... The potential benefits of leveraging artificial intelligence (A) in the physical security industry have pros and cons on both ... In the end, it will be the combined power of AI and human intelligence that will allow us to combat todays constantly changing ...
Despite the public debate between Elon Musk and Mark Zuckerberg on whether or not artificial intelligence (AI) is good for ... smackdown over the possible threat of artificial intelligence. (AP Photo/Manu Fernandez, Stephan Savoia) ...
Practically every industry has something to gain from artificial intelligence and machine learning. Explore how SAS solutions ... Latest features make it easier for you to innovate with artificial intelligence.. ...
suddenly you see through it like a pane of glass - ah the path. Then the coding. The debugging is enough to drive you insane. The slightest most subtle error can take days to find and then you feel so stupid for it was in plane sight all the time. All of that requires the concept of how to accomplish a task. But how do you create emotion? That is different. Now you are talking about the freedom to just act arbitrarily. Of I could mimic a random thought generator seeded with the timer taking the last digit of the second. But that only creates the appearance of randomness. In programming, it is IMPOSSIBLE to create a true random generator for you quickly discover, whatever the project, it will fall back into as cycle for pure randomness cannot be coded.. I do not even know where to begin to try to create REAL human emotion since it is impossible to create randomness. I can mimic human emotion. You will get to see some of that in the final launch of Socrates. He can even joke. If you want to buy ...
... ligència artificial (ca); artificial intelligence researcher (en); باحث في مجال الذكاء الاصطناعي (ar); ερευνητής τεχνητής ... Media in category "Artificial intelligence researchers". The following 81 files are in this category, out of 81 total. ... investigadora de la inteligencia artificial, investigador de inteligencia artificial, investigadora de inteligencia artificial ... Meredith Whittaker at House Hearing on Artificial Intelligence.jpg 1,275 × 1,103; 164 KB. ...
... and advances in artificial intelligence will only increase the accuracy of this technique. ... What is artificial intelligence (AI)?. Artificial intelligence is an umbrella term encompassing both machine learning and ... Artificial Intelligence in Histopathology. News-Medical. https://www.news-medical.net/life-sciences/Artificial-Intelligence-in ... Artificial intelligence can be applied to detect and count cells, for example in mitotic events which may be relevant for ...
Advances in Artificial Intelligence is a peer-reviewed, Open Access journal that investigates the role of artificial ... intelligence in this rapidly progressing and challenging environment. It provides a rich, multidisciplinary platform for ... S. M. Potter, "What can artificial intelligence get from neuroscience?" in Artificial Intelligence Festschrift: The Next 50 ... M. A. Boden, "Creativity and artificial intelligence," Artificial Intelligence, vol. 103, no. 1-2, pp. 347-356, 1998. View at ...
Industrial products executives view artificial intelligence (AI)/cognitive as market-ready, and well over half say the industry ... The artificial intelligence effect on industrial products: Profiting from an abundance of data ... By expanding digital intelligence adoption, AI technologies can help executives translate data into insights to drive greater ...
Call for Participation in AI KR (Artificial Intelligence Knowledge Representation) Community Group. W3C Team , Posted on: July ... The AI KR (Artificial Intelligence Knowledge Representation) Community Group has been launched:. The overall goal/mission of ... Should Explainable AI be applied to more general artificial intelligence - such as AGI but not restricted to - rather than just ... An open W3C community group called AIKR which stands for Artificial Intelligence Knowledge Representation was started around ...
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... On June 7 2019 the exhibition "Artificial Intelligence and Intercultural ... he working principle of generative-adversarial networks has brought artificial intelligence close to human thinking. This ... dedicated to the creative capabilities of Artificial Intelligence (AI) will be open at the General Staff Building. ...
artificial emotions. The failure of artificial intelligence. Cyberlife Research. Steve Grand. In defense of robot domination. ... Walterian Creatures: the next step in the Evolution of Intelligence?. The Birth of Artificial Intelligence. When It Changed. ... Emergent Artificial Intelligence. Instead, a holistic view can be argued- that the only example we have of intelligence ... Prelude: Knowledge-based Artificial Intelligence. As AI research began to organise into a coherent subject in the 1950s and 60s ...
1 Intuition of Artificial Intelligence. 1.1 What is Artificial Intelligence?. 1.1.1 A Definition of Artificial Intelligence. ... 1.4 Intuition of Artificial Intelligence Concepts. 1.4.1 Narrow Intelligence - Specific purpose solutions. ... Grokking Artificial Intelligence Algorithms opens the lid on AIs black box, shining a light on how AI algorithms work and how ... confirm your purchase of Grokking Artificial Intelligence Algorithms pBook + eBook + liveBook Well charge your credit card for ...
... מאמר בנושא: האם הופכת התבונה לתכונה אפשרית של מכונה? ... You just viewed בינה מלאכותית - (AI (Artificial.... Please take a moment to rate this material. ...
... We are pleased to present a new Special Issue on Artificial Intelligence in ... or artificial life. Proper image processing, appropriate selection of features and artificial intelligence method can support ... Artificial intelligence is increasingly used in various fields of life. One such area is medicine. Modern medical imaging ... Computer-aided detection in chest radiography based on artificial intelligence: a survey As the most common examination tool in ...
To Advance Artificial Intelligence, Reverse-Engineer the Brain. Opinion: Progress in deep learning research will come from the ... These layers inspired the pursuit of artificial intelligence in the 1950s. But the most important layers are the many floors ... Imagine human intelligence as a skyscraper. Instead of girders and concrete, this structure is built with algorithms, or ... These are the algorithms of everyday intelligence that are at work every time we recognize someone we know, tune in to a single ...
Artificial intelligence is a transformative technology that will drive sustainable competitive advantage and business value. IT ... Artificial intelligence is a transformative technology that will drive sustainable competitive advantage and business value. IT ... China Summary Translation: Artificial Intelligence Primer for 2018 Published: 29 May 2018 ...
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How Artificial Intelligence Will Change Medicine. By channeling a flood of biomedical data, machine learning could transform ... Despite fears that machines will displace humans, most experts believe artificial and human intelligence will work ... but it has become clear that we can learn much more with an assist from artificial intelligence. Over the next decade deep- ...
Scientists are working on a circuit that mimics the human brain in an effort to dramatically boost artificial intelligence and ... Brain-like circuit could drive artificial intelligence. Using artificial synapses could push machine learning and image ... Scientists are working on a circuit that mimics the human brain in an effort to dramatically boost artificial intelligence and ... at the University of California at Santa Barbara said this week they have created a circuit running about 100 artificial ...
  • This will also employ more sophisticated automatic learning and artificial intelligence algorithms to predict patient response to immunotherapy. (eurekalert.org)
  • We have reached the point where pattern-recognition algorithms and artificial intelligence (A.I.) are more accurate than humans at the visual diagnosis and observation of X-rays, stained breast cancer slides and other medical signs involving general correlations between normal and abnormal health patterns. (leadersneedpancakes.com)
  • They received research assistance from 30 Stanford law, computer science, and engineering students, and five NYU Law students, who participated in the Spring 2019 Stanford policy lab, Administering by Algorithm: Artificial Intelligence in the Regulatory State . (bespacific.com)
  • SAN FRANCISCO, CA - September 21, 2017 - Today Square announced that Naveen Rao, Corporate Vice President and General Manager of the Artificial Intelligence Products Group at Intel Corporation, has joined its Board of Directors. (squareup.com)
  • Rao currently serves as Corporate Vice President and General Manager of the Artificial Intelligence Products Group at Intel, after serving as Vice President and General Manager of Artificial Intelligence Solutions from August 2016 to March 2017. (squareup.com)
  • What will 2017 have in store for artificial intelligence? (leadersneedpancakes.com)
  • Elon Musk and others launched OpenAI , to discover and enact the path to safe artificial general intelligence in 2015 - to find a friendly A.I. In early 2016, Google's DeepMind defeated legendary Go player Lee Se-dol in a historic victory. (leadersneedpancakes.com)
  • In Dr. Daniel Kühlwein, staff member of the Center of Excellence for Artificial Intelligence at the global consulting firm Capgemini, we were able to convince an expert in the field of artificial intelligence for cooperation. (medizin-aspekte.de)
  • In 1959, MIT began research in the field of artificial intelligence. (leadersneedpancakes.com)
  • Finally, some researchers see intelligence as a quality that can only be acquired and demonstrated through relationship with other intelligent beings. (encyclopedia.com)
  • By designing an algorithm and developing it to analyse CT scan images, medical researchers at Gustave Roussy, CentraleSupélec, Inserm, Paris-Sud University and TheraPanacea (spin-off from CentraleSupélec specialising in artificial intelligence in oncology-radiotherapy and precision medicine) have created a so-called radiomic signature. (eurekalert.org)
  • The use of Cognitive Analytics/Artificial Intelligence (AI) Systems is set to accelerate, with the expectation that it'll be considered 'mainstream' in the next 5 - 10 years. (wiley.com)
  • Cognitive Analysis and AI prepares business users for the era of cognitive analytics / artificial intelligence. (wiley.com)
  • Research in artificial intelligence (AI), which includes machine learning (ML), computer vision (CV), and natural language processing (NLP), aims to develop and analyze computational approaches to automated reasoning in the presence of uncertainties. (arizona.edu)
  • Founded in 1962, The Stanford Artificial Intelligence Laboratory (SAIL) has been a center of excellence for Artificial Intelligence research, teaching, theory, and practice for over fifty years. (stanford.edu)
  • Expert in Artificial Intelligence and have done many similar Academic writing, research reports, essays and advance essays. (freelancer.com.au)
  • This new ERS post talks about a new research that has incorporated the use of artificial intelligence, AI, in Pulmonary Function Testing, PFT, interpretations. (wordpress.com)
  • The field of AI is considered to have its origin in the publication of British mathematician Alan Turing's (1912 - 1954) paper "Computing Machinery and Intelligence" (1950). (encyclopedia.com)
  • Teachable robots solve kid-built mazes with artificial intelligence. (kickstarter.com)
  • Artificial intelligence (AI) is the field within computer science that seeks to explain and to emulate, through mechanical or computational processes, some or all aspects of human intelligence. (encyclopedia.com)
  • Each of these understandings of intelligence has been used as the basis of an approach to developing computer programs with intelligent characteristics. (encyclopedia.com)
  • In addition to tracking mood and contextual data, the artificial intelligence customer service can also search the web to help answer requests. (trendhunter.com)
  • While there are many subfields to artificial intelligence this work seeks to identify the most commonly applied AI techniques to financial investing as appears in academic literature. (igi-global.com)
  • We have trained the artificial intelligence to identify components that are unique to cancer patients, and also the Achilles heel proteins of the pathogens that we're analysing. (europeanceo.com)
  • there is no agreed upon definition of artificial intelligence, primarily because there is little agreement as to what constitutes intelligence. (encyclopedia.com)
  • The challenge with artificial intelligence is that no single and agreed-upon definition exists. (leadersneedpancakes.com)
  • Machine learning is a branch of artificial intelligence science i.e. the systems that can learn data. (techrepublic.com)
  • How do CIOs get a grip on what's practical versus theoretical in the dynamic space of machine intelligence? (leadersneedpancakes.com)
  • Artificial Intelligence and Machine Learning in Lower Extremity Arthroplasty: A Review. (ox.ac.uk)
  • BACKGROUND: Driven by the rapid development of big data and processing power, artificial intelligence and machine learning (ML) applications are poised to expand orthopedic surgery frontiers. (ox.ac.uk)
  • The study is conducted to evaluate the adaptability of artificial intelligence in recruitment and to assess the effect of this technology on the performance of the employees. (scirp.org)
  • Before founding Nervana in 2014, Rao was a neuromorphic machines researcher at Qualcomm Inc., where he focused on neural computation and learning in artificial systems. (squareup.com)
  • Washington, D.C., Stanford, Calif., and New York, February 18, 2020 - The Administrative Conference of the United States (ACUS), Stanford Law School , and New York University School of Law are pleased to announce the release of a major report exploring federal agencies' use of artificial intelligence (AI) to carry out administrative law functions. (bespacific.com)
  • Artificial intelligence techniques have long been applied to financial investing scenarios to determine market inefficiencies, criteria for credit scoring, and bankruptcy prediction, to name a few. (igi-global.com)
  • Future trends will continue to integrate hybrid artificial intelligence techniques into financial investing, portfolio optimization, and risk management. (igi-global.com)
  • Well we're using artificial intelligence and supercomputers to analyse the genomes of humans or bacteria. (europeanceo.com)
  • Standard Multiple Linear regression model is used to predict the performance of the employees and one-way ANOVA is used to compare the artificial intelligence based recruitment with performance indicating variables namely reliability, productivity, Automation, Gamification & Training using SPSS. (scirp.org)
  • RESULTS: A narrative review of artificial intelligence and ML developments is summarized with specific applications to lower extremity arthroplasty, with specific lessons learned from osteoarthritis gait models, joint-specific imaging analysis, and value-based payment models. (ox.ac.uk)
  • Artificial Intelligence is an innovative technology emerging trend that can be witnessed in Human Resource technology, especially can be very effective and beneficial in the area of recruitment. (scirp.org)