Neural Networks (Computer)
Decision Making, Computer-Assisted
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)
Types of Cognition Disorders: There are several types of cognitive disorders that affect different aspects of cognitive functioning. Some common types include:
1. Attention Deficit Hyperactivity Disorder (ADHD): Characterized by symptoms of inattention, hyperactivity, and impulsivity.
2. Traumatic Brain Injury (TBI): Caused by a blow or jolt to the head that disrupts brain function, resulting in cognitive, emotional, and behavioral changes.
3. Alzheimer's Disease: A progressive neurodegenerative disorder characterized by memory loss, confusion, and difficulty with communication.
4. Stroke: A condition where blood flow to the brain is interrupted, leading to cognitive impairment and other symptoms.
5. Parkinson's Disease: A neurodegenerative disorder that affects movement, balance, and cognition.
6. Huntington's Disease: An inherited disorder that causes progressive damage to the brain, leading to cognitive decline and other symptoms.
7. Frontotemporal Dementia (FTD): A group of neurodegenerative disorders characterized by changes in personality, behavior, and language.
8. Post-Traumatic Stress Disorder (PTSD): A condition that develops after a traumatic event, characterized by symptoms such as anxiety, avoidance, and hypervigilance.
9. Mild Cognitive Impairment (MCI): A condition characterized by memory loss and other cognitive symptoms that are more severe than normal age-related changes but not severe enough to interfere with daily life.
Causes and Risk Factors: The causes of cognition disorders can vary depending on the specific disorder, but some common risk factors include:
1. Genetics: Many cognitive disorders have a genetic component, such as Alzheimer's disease, Parkinson's disease, and Huntington's disease.
2. Age: As people age, their risk of developing cognitive disorders increases, such as Alzheimer's disease, vascular dementia, and frontotemporal dementia.
3. Lifestyle factors: Factors such as physical inactivity, smoking, and poor diet can increase the risk of cognitive decline and dementia.
4. Traumatic brain injury: A severe blow to the head or a traumatic brain injury can increase the risk of developing cognitive disorders, such as chronic traumatic encephalopathy (CTE).
5. Infections: Certain infections, such as meningitis and encephalitis, can cause cognitive disorders if they damage the brain tissue.
6. Stroke or other cardiovascular conditions: A stroke or other cardiovascular conditions can cause cognitive disorders by damaging the blood vessels in the brain.
7. Chronic substance abuse: Long-term use of drugs or alcohol can damage the brain and increase the risk of cognitive disorders, such as dementia.
8. Sleep disorders: Sleep disorders, such as sleep apnea, can increase the risk of cognitive disorders, such as dementia.
9. Depression and anxiety: Mental health conditions, such as depression and anxiety, can increase the risk of cognitive decline and dementia.
10. Environmental factors: Exposure to certain environmental toxins, such as pesticides and heavy metals, has been linked to an increased risk of cognitive disorders.
It's important to note that not everyone with these risk factors will develop a cognitive disorder, and some people without any known risk factors can still develop a cognitive disorder. If you have concerns about your cognitive health, it's important to speak with a healthcare professional for proper evaluation and diagnosis.
There are various causes of intellectual disability, including:
1. Genetic disorders, such as Down syndrome, Fragile X syndrome, and Turner syndrome.
2. Congenital conditions, such as microcephaly and hydrocephalus.
3. Brain injuries, such as traumatic brain injury or hypoxic-ischemic injury.
4. Infections, such as meningitis or encephalitis.
5. Nutritional deficiencies, such as iron deficiency or iodine deficiency.
Intellectual disability can result in a range of cognitive and functional impairments, including:
1. Delayed language development and difficulty with communication.
2. Difficulty with social interactions and adapting to new situations.
3. Limited problem-solving skills and difficulty with abstract thinking.
4. Slow learning and memory difficulties.
5. Difficulty with fine motor skills and coordination.
There is no cure for intellectual disability, but early identification and intervention can significantly improve outcomes. Treatment options may include:
1. Special education programs tailored to the individual's needs.
2. Behavioral therapies, such as applied behavior analysis (ABA) and positive behavior support (PBS).
3. Speech and language therapy.
4. Occupational therapy to improve daily living skills.
5. Medications to manage associated behaviors or symptoms.
It is essential to recognize that intellectual disability is a lifelong condition, but with appropriate support and resources, individuals with ID can lead fulfilling lives and reach their full potential.
Artificial Intelligence (series)
Artificial intelligence marketing
Norm (artificial intelligence)
Symbolic artificial intelligence
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Friendly artificial intelligence
Operational artificial intelligence
Diagnosis (artificial intelligence)
Artificial Intelligence (EP)
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Artificial Intelligence (journal)
Artificial Intelligence II
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Artificial general intelligence
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Ablation (artificial intelligence)
Explainable artificial intelligence
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Artificial intelligence of things
History of artificial intelligence
Frame semantics (linguistics)
Sniper Ghost Warrior Contracts
Mushroom Wars 2
USS Mullany (DD-528)
RAAF Operations Building Site
Automated planning and scheduling
University of Technology Sydney
Artificial Intelligence Versus Human-Controlled Doctor in Virtual Reality Simulation for Sepsis Team Training: Randomized...
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Promising Future, Complex Past: Artificial Intelligence and the Legacy of Physiognomy
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No. 1: Twenty-Eighth AAAI Conference On Artificial Intelligence Archives - AAAI
- In 2022, artificial-intelligence firms produced an overwhelming spectacle, a rolling carnival of new demonstrations. (nymag.com)
Bridge to Artificial Intelligence3
- The NIH Common Fund's Bridge to Artificial Intelligence program (Bridge2AI) aims to bridge the gap between biomedical and behavioral research and artificial intelligence (AI). (nih.gov)
- The NIH Common Fund's Bridge to Artificial Intelligence (Bridge2AI) program will propel biomedical research forward by setting the stage for widespread adoption of artificial intelligence (AI) that tackles complex biomedical challenges beyond human intuition. (nih.gov)
- A new NIH Common Fund program, called Bridge to Artificial Intelligence (Bridge2AI) , will invest about $100 million over four years to tap into the power of AI to advance research to inform clinical decisions and individualize care. (nih.gov)
- Mimicking biological nervous systems, artificial neural networks have been used successfully to recognize and predict patterns of neural signals involved in brain function. (nih.gov)
- The researchers used recent advances in technology, such as more powerful graphical processing units in computers and artificial neural networks, to develop an automated reconstruction process. (nih.gov)
- artificial neural networks simulate the actual neural networks in the human brain. (versus.com)
- The authors explore whether an object-detection model trained on artificial images could evaluate real images as an automated target recognition system, an important advancement in artificial intelligence and machine learning for the U.S military. (rand.org)
- Next weekend, the team will present their research at the Association for the Advancement of Artificial Intelligence's 30th Conference on Artificial Intelligence. (cbsnews.com)
- There has been continued advancement of artificial intelligence and machine learning for analyzing big data. (nationaldefensemagazine.org)
- Copertari, L. (2019) On Natural and Artificial Intelligence. (scirp.org)
- A machine learning approach modeled after the brain in which algorithms process signals via interconnected nodes called artificial neurons. (nih.gov)
- And, to some computing experts, it is evidence that the industry is on the verge of reaching a long-awaited, much-hyped milestone: Artificial General Intelligence. (motherjones.com)
- The researchers, with a diverse array of expertise including computer science, electrical engineering and earth systems science, found that they can use artificial intelligence to identify global poverty zones by comparing daytime against nighttime satellite images. (cbsnews.com)
- At present, the intelligence of urban management has become a very hot topic, and many researchers have launched them. (hindawi.com)
- Researchers are reporting that artificial intelligence (AI) has been used for the first time to instantly and accurately measure blood flow. (nih.gov)
- The data will be used to train an artificial intelligence network to help predict changes in blood glucose levels before they occur. (nih.gov)
- Therefore, the application of artificial intelligence to the research of sponge city has both theoretical and practical significance. (hindawi.com)
- The application of artificial intelligence to the research of sponge city, in other applications, artificial intelligence is often used as a high-tech research, and this paper is committed to deeply explore the characteristics of artificial intelligence applied in the sponge city management mode. (hindawi.com)
- Support research that uses Artificial Intelligence (AI) and deep learning approaches for discovery and translational research. (nih.gov)
- Artificial intelligence is also applied in research in other disciplines. (rug.nl)
- You will round off your bachelor's degree with a small research project (15 ECTS), which you will complete under supervision of a researcher in the field of Artificial Intelligence at the Bernoulli Institute. (rug.nl)
- The White House Office of Science and Technology Policy and National Science Foundation are looking for your input to shape the work of the National Artificial Intelligence Research Resource (NAIRR) Task Force. (nih.gov)
- It is not often that you are obliged to proclaim a much-loved genius wrong, but in his alarming prediction on artificial intelligence and the future of humankind, I believe Stephen Hawking has erred. (newscientist.com)
- Artificial intelligence (AI) applies technology to make computers (seem to) act rationally. (cdc.gov)
- Technology, machines, and software that have the ability to be self-directed and learn from their actions are generally known as artificial intelligence. (rand.org)
- The current state of the art in knowledge and technology concerning natural and artificial intelligence is innovatively discussed here. (scirp.org)
- So it might come as a surprise that in the military and intelligence agencies, the technology is not moving as fast as it could. (nationaldefensemagazine.org)
- Even as their needs for data analysis continue to grow, the U.S. military and intelligence communities are not harnessing machine learning technology to its full potential, says Brian Wilson, senior vice president of Zenoss, an information technology company that does business in both the commercial and government sectors. (nationaldefensemagazine.org)
- We've all seen artificial technology at play," says astrophysicist Neil DeGrasse Tyson, a member of the Defense Innovation Board. (nationaldefensemagazine.org)
- Peter Kellman from the National Institutes of Health (NIH) in the United States, who working with Hui Xue at the NIH, developed the automated AI techniques to analyze the images that were used in the study, said: "This study demonstrates the growing potential of artificial intelligence-assisted imaging technology to improve the detection of heart disease and may move clinicians closer to a precision medicine approach to optimize patient care. (nih.gov)
- Last month, DeepMind, a subsidiary of technology giant Alphabet, set Silicon Valley abuzz when it announced Gato , perhaps the most versatile artificial intelligence model in existence. (motherjones.com)
- In the international Bachelor's degree programme in Artificial Intelligence you will study existing intelligence as we see it in the world and develop 'intelligent' and user-friendly products. (rug.nl)
- This international degree programme focuses on human thinking, artificial thinking (computers, robots) and behaviour in social systems (e.g. group behaviour). (rug.nl)
- Whereas ordinary artificial intelligence has to be pre-trained or programmed to solve a specific set of problems, a general intelligence can learn through intuition and experience. (motherjones.com)
- Artificial intelligence (AI) has contributed substantially to the resolution of a variety of biomedical problems, including cancer, over the past decade. (nih.gov)
- Though still in its infancy as a field, artificial intelligence (AI) is poised to transform the practice of medicine and the delivery of healthcare. (cdc.gov)
- This is precisely because current AI is not akin to human intelligence, and poorly designed autonomous systems have the potential to rapidly escalate dangerous situations to catastrophic conclusions when pitted against each other. (newscientist.com)
- With the advent of more powerful computers and sky surveys that generate unimaginable quantities of data, artificial intelligence is the go-to tool for the keen researcher of space. (astronomy.com)
- The purpose of this article is, based on artificial intelligence, to study the analysis of wisdom management models in sponges. (hindawi.com)
- As today's urbanization management is very superior, the study of how managers use artificial intelligence to manage a city quickly and effectively and how to control the various problems in the city, which is also of profound significance for the development and expansion of artificial intelligence. (hindawi.com)
- In recent years, scholars have studied the theme of sponge city, but relatively few of them have applied artificial intelligence to study the management mode of the sponge city. (hindawi.com)
- This glossary of artificial intelligence is a list of definitions of terms and concepts relevant to the study of artificial intelligence , its sub-disciplines, and related fields. (wikiwand.com)
- The study also showed that an artificial intelligence (AI)-based system was effective in assessing those same smartphone images to accurately flag babies needing ROP care. (nih.gov)
- Stephen Hawking thinks computers may surpass human intelligence and take over the world. (newscientist.com)
- There is a wide range of views about how urgent or profound the policy questions raised by general, "human level", artificial intelligence may be. (eff.org)
- AI refers to a broad range of computational methods that mimic human intelligence. (nih.gov)
- China's quest to become the global center for artificial intelligence starts with mastering big data analytics. (rand.org)
- ORLANDO - The use of artificial intelligence during colonoscopy appears to boost the accuracy and sensitivity of adenoma detection, even for lesions as small as 5 mm, according to recent studies. (medscape.com)
- Artificial intelligence for polyp detection has the potential to help all colonoscopists achieve detection rates closer to true prevalence, and to further reduce the risk of interval colorectal cancers," he added. (medscape.com)
- This article focuses on what is novel about the world of artificial intelligence and privacy, arguing that the chief novelty lies in the potential for data persistence, data repurposing and data spillovers. (nber.org)
- This lecture addresses the potential links between AI and religious belief, which include the question of whether an artificial "superintelligence", were one to arise, would be well-disposed towards us. (gresham.ac.uk)
- The evolving field of Artificial Intelligence (AI) has the potential to revolutionize scientific discovery and extend diagnostic capabilities to remote, underserved settings. (nih.gov)
- CDC's Data Modernization Initiative supports artificial intelligence (AI), machine learning (ML) and other powerful solutions for large or complex data. (cdc.gov)
- Artificial intelligence can use an individual's data to make predictions about what they might desire, be influenced by, or do. (nber.org)
- Artificial Intelligence (AI) is essential to enhancing our computing competencies to address emerging requirements for the automation and data centric world. (renesas.com)
- This paper first introduces the artificial intelligence algorithm and sponge city, then compares the traditional sponge city and the wisdom sponge city, then creates a LSTM neural network model, introducing artificial intelligence into sponge city intelligent dynamics in the analysis, and finally compares the rainfall data analysis to the ground. (hindawi.com)
- Artificial Intelligence draws on knowledge from various disciplines, such as cognitive psychology, linguistics, data science, computing science, logic and philosophy, and teaches you to apply this knowledge in smart digital systems. (rug.nl)
- Unlike ordinary AI, Artificial General Intelligence wouldn't require giant troves of data to learn a task. (motherjones.com)
- On this computer science with artificial intelligence course, you'll learn to design and build the AI programs and systems behind these exciting developments. (southampton.ac.uk)
- Machine learning is a type of Artificial Intelligence (AI) that provides machines (like computers) the ability to automatically learn and improve from experience, without being explicitly programmed. (nih.gov)
- Chances are you've heard the terms "artificial intelligence" and "machine learning" thrown around recently, and while they are often used together, they actually refer to different things. (astronomy.com)
- What rules, if any, should constrain the use of machine learning methods when coupled to the large scale surveillance technologies operated by intelligence agencies? (eff.org)
- This would require deep machine learning and artificial intelligence. (nationaldefensemagazine.org)
- The 20-member panel of tech industry and government officials, established in April by Defense Secretary Ash Carter, last month offered a new set of recommendations, one of which is to "catalyze innovations in artificial intelligence and machine learning. (nationaldefensemagazine.org)
- The board characterized artificial intelligence and machine learning as "important, defining technologies. (nationaldefensemagazine.org)
- Outside advisers have urged the Defense Department to become more aggressive in the use of artificial intelligence not only to increase its capabilities but also to save money. (nationaldefensemagazine.org)
- The paper goes from concepts of natural intelligence to ideas about the possible nature and future of artificial intelligence. (scirp.org)
- A rtificial Intelligence ( AI ) is a high-stakes business priority, with companies spending $306 billion on AI applications in the past three years. (accenture.com)
- The National Institute of Biomedical Imaging and Bioengineering (NIBIB) will hold a Workshop on Artificial Intelligence in Medical Imaging to foster innovative collaborations in applications for diagnostic medical imaging. (nih.gov)
- Another computer-aided system, known as EndoBRAIN artificial intelligence, is easy to use and provides an automatic diagnosis at the push of a button, reported Yuichi Mori, MD, from Showa University in Shinagawa-ku, Japan. (medscape.com)
- Hyper-intelligence machines have permeated every layer of modern society - from smartphones to self-driving cars. (nationaldefensemagazine.org)
- In the first year you will acquire knowledge of the most important disciplines for artificial intelligence. (rug.nl)
- The aim is to support the perception of artificial intelligence in the radiation therapy landscape. (nih.gov)
- Porteus, like many of his cohorts, believed that differences in intelligence testing results supported erroneous ideas about the inferiority of neurodivergent people, women, people of color, and other marginalized groups. (nih.gov)
- Is Artificial Intelligence Real? (versus.com)
- The innovation of this paper lies in the following: (1) In the management of cities, that is, in the sponge city management mode, artificial intelligence can be used to make a comprehensive and effective choice. (hindawi.com)
- The addition of artificial intelligence to the urban management mode brings more convenience and optimization to the urban management, to form a sponge city intelligent management mode based on artificial intelligence. (hindawi.com)