Artificial Intelligence: 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.Intelligence: The ability to learn and to deal with new situations and to deal effectively with tasks involving abstractions.Expert Systems: 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.Fuzzy Logic: 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.Neural Networks (Computer): 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.Chloroprene: Toxic, possibly carcinogenic, monomer of neoprene, a synthetic rubber; causes damage to skin, lungs, CNS, kidneys, liver, blood cells and fetuses. Synonym: 2-chlorobutadiene.Decision Making, Computer-Assisted: 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.Intelligence Tests: Standardized tests that measure the present general ability or aptitude for intellectual performance.Diagnosis, Computer-Assisted: Application of computer programs designed to assist the physician in solving a diagnostic problem.Emotional Intelligence: 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.Algorithms: A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task.Computer Simulation: Computer-based representation of physical systems and phenomena such as chemical processes.Wechsler Scales: Tests designed to measure intellectual functioning in children and adults.Software: Sequential operating programs and data which instruct the functioning of a digital computer.Cognition: Intellectual or mental process whereby an organism obtains knowledge.Stanford-Binet Test: An individual intelligence test designed primarily for school children to predict school performance and the ability to adjust to everyday demands.Neuropsychological Tests: 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.Cognition Disorders: Disturbances in mental processes related to learning, thinking, reasoning, and judgment.Child Development: The continuous sequential physiological and psychological maturing of an individual from birth up to but not including ADOLESCENCE.Intellectual Disability: 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)Problem Solving: A learning situation involving more than one alternative from which a selection is made in order to attain a specific goal.Executive Function: 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.

*  Journals in Artificial Intelligence

Artificial Intelligence - Books, Journals, Electronic Media from Springer ... Annals of Mathematics and Artificial Intelligence. Editor-in-Chief: Martin Golumbic ISSN Print: 1012-2443 ISSN Online: 1573- ... Artificial Intelligence and Law. Editors-in-Chief: K.D. Ashley; T. Bench-Capon; G. Sartor ... Applied Intelligence. The International Journal of Research on Intelligent Systems for Real Life Complex Problems ...

*  Artificial Intelligence and Ethics

"Artificial Intelligence Is Changing the World, and Humankind Must Adapt", "Physicist Louis Del Monte believes that by 2045 ... Copyright © 1995-2014 Association for the Advancement of Artificial Intelligence.. Your use of this site is subject to our ... which go to the center of the quest to build AI systems with potentially super-human intelligence. ...

*  Inside Microsoft's Artificial Intelligence Comeback | WIRED

The great irony here is that artificial intelligence was once Microsoft's game to lose. Dating back to the early 1990s, the ... As one of the three intellects who shaped the deep learning that now dominates artificial intelligence, he has been catapulted ... Outside the company, he's been instrumental in building the Partnership on Artificial Intelligence, a consortium that is ... artificial intelligence will require us to imagine how computing works all over again. That's why Mark Zuckerberg made it his ...

*  Artificial Intelligence and Financial Services

The author surveys key requirements and specific design techniques for artificial intelligence (AI) applications in the ... L.F. Pau, "Artificial Intelligence and Financial Services", IEEE Transactions on Knowledge & Data Engineering, vol. 3, no. , pp ... p,The author surveys key requirements and specific design techniques for artificial intelligence (AI) applications in the ... conflict resolution strategies; financial services; specific design techniques; artificial intelligence; decision technology; ...

*  Locating Missing and Exploited Children with Artificial Intelligence

Artificial intelligence will help us augment the efforts of our analysts, who are looking for missing and exploited children.. ... describes the resource challenges in processing and extracting intelligence from the volume of missing child reports it ...

*  Adobe Sensei | Unified artificial intelligence and machine learning

It uses artificial intelligence (AI) and machine learning to help you discover opportunities that are hidden, make tedious ... Adobe Sensei puts artificial intelligence at the center of amazing customer experiences.. ... Adobe Sensei is the intelligence that will change the way you do business and the way customers experience your business. ...

*  Environmental Decision Support Systems and Artificial Intelligence

Environmental Decision Support Systems and Artificial Intelligence. Papers from the AAAI Workshop. Ulises Corté and Miquel ... Copyright © 1995-2014 Association for the Advancement of Artificial Intelligence.. Your use of this site is subject to our ...

*  Google buys artificial-intelligence firm DeepMind - MarketWatch

GOOG, -0.57% has acquired artificial-intelligence firm DeepMind Technologies Ltd., reports said Monday, with a Recode report ...

*  Aims and Scope: Artificial Intelligence and Law

Aims and Scope: Artificial Intelligence and Law. Artificial Intelligence and Law is an international forum for the ... Financial support for the Journal of Artificial Intelligence and Law is provided by the University of Pittsburgh School of Law. ... Studies which address the legal, ethical and social implications of the field of Artificial Intelligence and Law.. Topics of ... In-depth studies of innovative artificial intelligence systems that are being used in the legal domain. ...

*  Collaboratively-Built Knowledge Sources and Artificial Intelligence

Collaboratively-Built Knowledge Sources and Artificial Intelligence. Papers from the 2010 AAAI Workshop. Vivi Nastase, Roberto ... Copyright © 1995-2014 Association for the Advancement of Artificial Intelligence.. Your use of this site is subject to our ... to promote the synergy between repositories of user-contributed knowledge and research in artificial intelligence. ...

*  M-P - Mcculloch-Pitts Neuron Model (artificial intelligence) | AcronymFinder

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.

*  "A knowledge-based system for temperature prediction in hot strip mills" by Haibo Xie, Zhengyi Jiang et al.

Rolling temperature is an important factor affecting mechanical properties of hot rolled strip significantly. Traditional techniques cannot meet higher precision control imperatives. In the present work, a novel knowledge-based system has been developed for the temperature prediction in hot strip mills. Neural network has been used for this purpose, which is an intelligent technique that can solve nonlinear problem of temperature control by learning from the samples. Furthermore, an annealing robust learning algorithm was presented to adjust the hidden node parameters as well as the weights of the adaptive neural networks. Simulations in a multi-object mode have been carried out to verify the effectivity of new neural optimization system. Calculation results confirm the feasibility of this approach and show a good agreement with experimental values obtained from a steel plant.

*  Optimization of Test Data for Basis Path Testing using Artificial Intelligence Techniques - ethesis

Software testing is a process carried out with the intent of finding errors. This helps in analyzing the stability and quality of a software. Stability and quality can be achieved by suitable test data. Test data can be generated either manually or by automated process. Manual generation of test data is a difficult task. It involves lot of effort due to presence of huge number of predicate nodes in a module. In this report, an automated process is proposed for test data generation in traditional methodology for the automatically constructed control flow graph. Code Coverage is a measure used in software testing process and is one of the key indicators of software quality. It helps the tester in evaluating the effectiveness of testing. It is achieved by automatically generating test data for various functions. Code coverage is not a method or a test; it is a measure which helps in improving software reliability. Effort has been made to gather code coverage information either by source code or by ...

*  Applying artificial intelligence to age prediction « The Diversity Blog - SaaS, Cloud & Business Strategy

Many technology commentators got all excited a few months ago when Microsoft launched, a website where users could upload a photo and the site would guess the age of the person in the picture. The service was a great way to showcase the opportunity that applying artificial intelligence to a problem set introduces.. Insilico hopes to deliver a similar sort of an offering, but with a far more important purpose.. Insilico Medicine is an organization focused on aging research. Headquartered at the Emerging Technology Centers at the Johns Hopkins University Eastern campus in Baltimore, it has R&D resources in Belgium, Poland, Russia and China employing 39 scientists worldwide. It is one of the leaders in artificial intelligence trained on some of the largest repositories of gene expression and pharmacological data. Its approach to aging research is to eschew animal testing and instead apply high-performance computing to the problem. ...

*  Artificial Intelligence | Free Internet Radio | TuneIn

Artificial Intelligence - Listen free online to streaming music stations, podcasts, and shows that often play Artificial Intelligence.

*  VUB Artificial Intelligence Lab

The Artificial Intelligence Laboratory at the Vrije Universiteit Brussel, or short VUB AI-Lab, was founded in 1983 by Prof. Dr. Luc Steels and is part of the Computer Science Department. Over the years, more than hundred researchers have worked at the laboratory. They have built a large number of artificial systems to investigate aspects of intelligence: knowledge systems, autonomous robots, machine learning systems, natural language processing components, design and implementation tools. Recently the AI lab has merged with the Computational Modeling Lab (COMO) headed by Prof. Dr. Ann Nowé and Prof. Dr. Bernard Manderick ...

*  Graduate Courses | Computer Science

CAP 5415 Principles and Algorithms of Computer Vision (3). Prerequisites: COP 4530 This course covers the basic computational principles and algorithms to extract information from images and image sequences. Topics include imaging models, linear and non-linear filtering, edge detection, stereopsis and motion estimation, texture modelling, segmentation and grouping, and deformable matching for recognition.. CAP 5605. Artificial Intelligence (3). Prerequisite: COP 4530. Introduction, representing knowledge, controlling attention, exploiting constraints, basic LISP programming, basic graph searching methods, game-playing and dealing with adversaries, understanding vision, theorem proving by computer, computer programs utilizing artificial intelligence techniques.. CAP 5638. Pattern Recognition (3). Prerequisite: Knowledge of probability and at least one programming language. Application of mathematical tools, in particular, probabilistic, ...

*  "Knowledge-Based Image Enhancement for Cooperative Tele-Assistance" by Erika Rogers, Versonya Dupont et al.

There is an increasing need in complex environments for computerized assistance, both for the effective filtering and display of pertinent information or data, and also for the decision-making task itself. The combination of artificial intelligence techniques with image processing and graphics capabilities provides the foundation for building intelligent systems which act as mediaries between the human and the task domain. In the field of tele-assistance, this type of system enables cooperative problem-solving between a remote semi-autonomous robot and a local human supervisor. This paper describes current work on such a system, with an emphasis on the development of knowledge-based image enhancement capabilities. These allow the intelligent assistant to request particular images related to a failure state, and to automatically enhance those images in such a manner that the local supervisor may quickly and effectively make a decision.

*  Artificial intelligence pioneer Marvin Minsky dead at 88 | Reuters

Marvin Minsky, the artificial intelligence pioneer who helped make machines think, leading to computers that understand spoken commands and beat grandmasters at chess, has died at the age of 88, the Massachusetts Institute of Technology said.

*  International Joint Conference on Artificial Intelligence | Project Ploughshares

On August 21, 116 robotics experts from 26 countries, including Canada, signed a letter calling for the United Nations to take action on the issue of lethal autonomous weapons systems, commonly known as killer robots. The letter comes at the start of the 2017 International Joint Conference on Artificial Intelligence (IJCAI) in Melbourne, Australia. An open letter signed by more … ...

*  Artificial intelligence customer service | AI mobile live chat CRM software provides artificial intelligence customer service software to help businesses connect with their customers and increase support team productivity.

*  Artificial Intelligence Has Race, Gender Biases - Slashdot

An anonymous reader shares a report: The ACLU has begun to worry that artificial intelligence is discriminatory based on race, gender and age. So it teamed up with computer science researchers to launch a program to promote applications of AI that protect rights and lead to equitable outcomes. MIT T...

*  Artificial Intelligence Has 'Great Potential, But We Need To Steer Carefully,' LinkedIn Co-founder Says - Slashdot

LinkedIn co-founder Reid Hoffman joined other tech moguls in voicing concern about artificial intelligence on Wednesday. From a report: 'It has great potential, but we need to steer carefully,' Hoffman said on Halftime Report. Hoffman stressed corporate transparency when asked what happens if compan...

*  Popularize Artificial Intelligence - PDF

Matteo Baldoni, Federico Chesani, Bernardo Magnini, Paola Mello, Marco Montali (eds.) Popularize Artificial Intelligence AI*IA Workshop and Prize for celebrating 100th anniversary of Alan Turing s birth,

*  BibMe: Generate Knowledge-Based Systems film / online video citations for your bibliography

If required by your instructor, you can add annotations to your citations. Just select Add Annotation while finalizing your citation. You can always edit a citation as well. ...

*  Applications and Innovations in Intelligent Systems XIV - | Richard Ellis | Apress

APPLICATIONS AND INNOVATIONS IN INTELLIGENT SYSTEMS XIV The papers in this volume are the refereed application papers presented at AI-2006, the

*  Protein subcellular localization : gene ontology based machine learning approaches | PolyU Institutional Research Archive

Based on mGOASVM, several more advanced multi-label predictors are proposed. These predictors further improve the performance of mGOASVM by enhancing the following aspects of the prediction process: 1. Classification Refinement. The classifier adopted by mGOASVM to tackle multi-label problems is rather primitive, thus refining the classification process is necessary. To this end, two multi-label predictors, namely AD-SVM and mPLR-Loc, are proposed. The former adopts an adaptive decision scheme for multi-label SVM classification. The scheme essentially converts the linear SVMs in the classifier into piecewise linear SVMs, which effectively reduces the over-prediction instances while having little influence on the correctly predicted ones, thus improving the prediction performance. The latter adopts a multi-label penalized logistic regression classifier equipped with an adaptive decision scheme, which can also boost the performance. 2. Deeper Feature Extraction. mGOASVM only considers the ...

*  IJNA, Editorial Board Member, International Journal of Dynamics of Fluids, Fluids Dynamics Journal, luids Dynamics Journals in...

Area of research/interest: Biomedical equipment technology,dielectrophoresis technique for cell separation and manipulation, therapeutic ultrasound and spectroscopic techniques.. Victor V. Moshchalkov, Laboratorium voor Vaste-Stoffysica en Magnetisme, KULeuven, Celestijnenlaan 200 D, B-3001 Leuven, Belgium. K.K. Pathak, Scientist & Advisor, Computer Simulation & Design Group, Advanced Materials and Processes Research Institute (CSIR), Bhopal 462026 (MP) INDIA Area of research/interest: Computational solid mechanics, metal forming, and casting simulations, structural shape optimization, artificial intelligence techniques.. K.S. Chan, City University of Hong Kong, Department of Physics, Hong Kong.. Gaoquan Shi, Department of Chemistry, Tsinghua University, Beijing 100084, P. R. China. Area of research/interest: Electrochemical fabrication of nanomaterials, Micro- andnanostructured conducting polymers and their nanocomposites, Sensors, actuators and solar cells based on ...

*  Machine learning - retrospective case study | Cochrane Heart

Question. Can machine learning reduce the time spent on screening abstracts and titles for Heart Group reviews?. Method. Active learning. Results. 39 reviews with a total of 146243 records screened to identify 1807 (1.2%) relevant records. This equals two researchers' full time working hours for 7 months. For a 100% recall, the mean percentage needed to screen fell between 1%-95%. In total, only 36% of records would have needed to be screened to identify all included records if this machine learning algorithm would have been used. This is equivalent to 874 hours of screening time, or roughly 3 months full time work by two researchers. We are still analysing the data and will aim to publish the full results in due course. Conclusions. Machine learning can save screening time but we found a great variability of performance across our reviews. ...

*  TaxProf Blog

Benjamin Alarie, Anthony Niblett & Albert Yoon (Toronto), Using Machine Learning to Predict Outcomes in Tax Law:. Recent advances in artificial intelligence and machine learning have bolstered the predictive power of data analytics. Research tools based on these developments will soon be commonplace. For the past two years, the three of us have been working on a project called Blue J Legal. We started with a view to understanding how machine learning techniques can be used to better predict legal outcomes. In this paper, we report on our experiences so far. The paper is set out in four parts.. In Part 1, we discuss the importance of prediction. In many fields, humans are outperformed by mechanical and algorithmic prediction. We explore this phenomenon and conclude that the legal field is no different. In Part 2, we discuss recent advances in machine learning that have generated powerful tools for prediction. These new methods outperform traditional statistical techniques in ...

*  Manning | Machine Learning in Action

A machine is said to learn when its performance improves with experience. Learning requires algorithms and programs that capture data and ferret out the interesting or useful patterns. Once the specialized domain of analysts and mathematicians, machine learning is becoming a skill needed by many.. Machine Learning in Action is a clearly written tutorial for developers. It avoids academic language and takes you straight to the techniques you'll use in your day-to-day work. Many (Python) examples present the core algorithms of statistical data processing, data analysis, and data visualization in code you can reuse. You'll understand the concepts and how they fit in with tactical tasks like classification, forecasting, recommendations, and higher-level features like summarization and simplification.. Readers need no prior experience with machine learning or statistical processing. Familiarity with Python is helpful.. ...

*  Demystifying Artificial Intelligence in Procurement - Spend Matters

Are you overwhelmed with the noise about AI right now? Is the buzzword meter ringing loudly for terms like cognitive, machine learning, chatbots, and RPA? Is it still a bit unclear what specific shorter-term and longer-term risk and opportunities are pertinent - and what's real out there right now? If so, you're not alone! ...

*  Design of a multi-signature ensemble classifier predicting neuroblastoma patients' outcome | BMC Bioinformatics | Full Text

We designed a new prognostic model based on a neuroblastoma classifier, NB-MuSE, that predicts patients' outcome by merging the biological and prognostic information of published gene expression signatures, assessed by a panel of machine learning algorithms, into a single outcome predictor. We examined every neuroblastoma-related signature described in the literature since 2002 without consideration for the purpose for which it was generated or the gene expression platform used. We took the blind screening approach to avoid biases and to include biology-driven signatures, not previously tested for patients stratification, in addition to risk-based signatures. We identified 33 signatures, complete of gene lists, suitable for our study. Patients' outcome was the final readout of the classifier and we had to develop a strategy to filter out poorly information signatures contributing to the background noise. We developed a multi-algorithm screening and an 80% accuracy filter for signature selection. ...

*  Fall 2012 Symposium on Artificial Intelligence of Humor

Human ability to communicate is incomplete without the use of humor. If a computational system is ever to approximate human communication ability or act as a competent partner in a conversation with a human, humor must be accounted for. The general goal of the proposed Symposium is to advance the state of the art in the direction of developing an AI system ("the system") capable of understanding the mechanism of a joke at a level sufficient for providing a punch line to a human generated setup (even if unintentional) and conversely, for computer reacting competently to a human generated punch line that follows a setup, generated by either participant. The effort is multidisciplinary in nature, and the participants from all of the contributing disciplines, viz., computational semantics, knowledge representation, computational psychology, AI theory, humanoid robotics, human-computer interface, human factors, to name just a few, are invited to participate. The Symposium will include a few invited ...

Mexican International Conference on Artificial Intelligence: MICAI (short for Mexican International Conference on Artificial Intelligence) is the name of an annual conference covering all areas of Artificial Intelligence (AI), held in Mexico. The first MICAI conference was held in 2000.Evolution of human intelligence: The evolution of human intelligence refers to a set of theories that attempt to explain how human intelligence has evolved and are closely tied to the evolution of the human brain and to the origin of language.Knowledge acquisition: Knowledge acquisition is the process used to define the rules and ontologies required for a knowledge-based system. The phrase was first used in conjunction with expert systems to describe the initial tasks associated with developing an expert system, namely finding and interviewing domain experts and capturing their knowledge via rules, objects, and frame-based ontologies.Vague setPhysical neural network: A physical neural network is a type of artificial neural network in which an electrically adjustable resistance material is used to emulate the function of a neural synapse. "Physical" neural network is used to emphasize the reliance on physical hardware used to emulate neurons as opposed to software-based approaches which simulate neural networks.ChloropreneComputer Support Services: Computer Support Services, Inc., or CSSI, is an multi-national company providing technology solutions and professional services.Computer-aided diagnosis: In radiology, computer-aided detection (CADe), also called computer-aided diagnosis (CADx), are procedures in medicine that assist doctors in the interpretation of medical images. Imaging techniques in X-ray, MRI, and Ultrasound diagnostics yield a great deal of information, which the radiologist has to analyze and evaluate comprehensively in a short time.Manas Kumar Mandal: Manas Kumar Mandal, is a scientist and psychologist who is the former director of the Defence Institute of Psychological Research, Delhi, India since January 5, 2004 to February, 2013. Presently he is Chief Controller (Life Sciences), Defence Research and Development Organisation; India.Clonal Selection Algorithm: In artificial immune systems, Clonal selection algorithms are a class of algorithms inspired by the clonal selection theory of acquired immunity that explains how B and T lymphocytes improve their response to antigens over time called affinity maturation. These algorithms focus on the Darwinian attributes of the theory where selection is inspired by the affinity of antigen-antibody interactions, reproduction is inspired by cell division, and variation is inspired by somatic hypermutation.Interval boundary element method: Interval boundary element method is classical boundary element method with the interval parameters.
Mac OS X Server 1.0Cognitive skill: Cognitive functioning is a term referring to a human’s ability to process to (thoughts) that should not deplete on a large scale in healthy individuals. Cognition mainly refers to things like memory, the ability to learn new information, speech, understanding of written material.Family aggregation: Family aggregation, also known as familial aggregation, is the clustering of certain traits, behaviors, or disorders within a given family. Family aggregation may arise because of genetic or environmental similarities.Repeatable Battery for the Assessment of Neuropsychological Status: The Repeatable Battery for the Assessment of Neuropsychological Status is a neuropsychological assessment initially introduced in 1998. It consists of ten subtests which give five scores, one for each of the five domains tested (immediate memory, visuospatial/constructional, language, attention, delayed memory).Postoperative cognitive dysfunction: Postoperative cognitive dysfunction (POCD) is a short-term decline in cognitive function (especially in memory and executive functions) that may last from a few days to a few weeks after surgery. In rare cases, this disorder may persist for several months after major surgery.David Rees Griffiths: David Rees Griffiths (November 6, 1882 – December 17, 1953), also known by his bardic name of Amanwy, was a Welsh poet, and an older brother of politician Jim Griffiths.Hyperphosphatasia with mental retardation syndrome: Hyperphosphatasia with mental retardation syndrome, HPMRS, also known as Mabry syndrome, has been described in patients recruited on four continents world-wide. Mabry syndrome was confirmed to represent an autosomal recessive syndrome characterized by severe mental retardation, considerably elevated serum levels of alkaline phosphatase, hypoplastic terminal phalanges, and distinct facial features that include: hypertelorism, a broad nasal bridge and a rectangular face.Behavior Rating Inventory of Executive Function: The Behavior Rating Inventory of Executive Function (BRIEF), developed by Gerard Gioia, Ph.D.

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

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:  (+info)

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

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)

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

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)

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

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)

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

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)

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

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)

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

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 ++.  (+info)

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

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)


  • on the contary, algorithms are usually pretty deterministic even if schochastic (e.g., looking for "answers") whereas "intelligence" - artificial or natural - implies some added ingredients such as creativity, innovation, novelty, new understanding, appreciation, etc. (


  • Then last September, Shum helmed a reorganization that blended researchers and product groups together to create one Artificial Intelligence and Research Group. (
  • In addition to original research contributions, the Journal will include a Book Review section, a series of Technology Reports describing existing and emerging products, applications and technologies, and a Research Notes section of occasional essays posing interesting and timely research challenges for the field of Artificial Intelligence and Law. (
  • As with the previous events, we believe work in this area should be encouraged, followed and popularized, to promote the synergy between repositories of user-contributed knowledge and research in artificial intelligence. (
  • The result of over 10 years of research and development, the ISA artificial intelligence core is based on many technical feats enabling continuous interaction with users, increased understanding and real-time intervention. (


  • The goal of this workshop is to provide a forum to discuss the ethical questions implicit in such headlines, which go to the center of the quest to build AI systems with potentially super-human intelligence. (
  • In-depth studies of innovative artificial intelligence systems that are being used in the legal domain. (


  • Theoretical or empirical studies in artificial intelligence (AI), cognitive psychology, jurisprudence, linguistics, or philosophy which address the development of formal or computational models of legal knowledge, reasoning, and decision making. (


  • Financial support for the Journal of Artificial Intelligence and Law is provided by the University of Pittsburgh School of Law. (


  • Artificial intelligence will help us augment the efforts of our analysts, who are looking for missing and exploited children. (
  • It uses artificial intelligence (AI) and machine learning to help you discover opportunities that are hidden, make tedious processes fast, and show you which data insights matter - and when they matter. (


  • The author surveys key requirements and specific design techniques for artificial intelligence (AI) applications in the financial services industry. (


  • Artificial & Machine Intelligence: Future Fact, or Fantasy? (


  • Studies which address the legal, ethical and social implications of the field of Artificial Intelligence and Law. (


  • In this, his latest very readable and entertaining book, Winter of the Genomes, author Larry Kilham explores and explains almost all aspects of the current state of development of robots and artificial intelligence (AI) and poses some very important questions: Where will humans fit in? (


  • AI Luminary Video: Michelle DeLaune, Senior VP/COO of the National Center for Missing and Exploited Children, describes the resource challenges in processing and extracting intelligence from the volume of missing child reports it receives. (
  • LOS ANGELES (MarketWatch) -- Google Inc. GOOG, -0.57% has acquired artificial-intelligence firm DeepMind Technologies Ltd., reports said Monday, with a Recode report citing a price of $400 million for the London-based start-up. (