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For the development of clinical decision support systems based on Bayesian networks, Mario A. Cypko investigates comprehensive expert;
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Handbook of Decision Support Systems for Neurological Disorders provides readers with complete coverage of advanced computer-aided;
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Bayesian decision analysis supports principled decision making in complex domains. This textbook takes the reader from a formal analysis;
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the major techniques currently available to build computer-assisted decision support systems. You will find practical solutions for;
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Bayesian and Decision Networks) and the advantages, both in terms of modeling and analysis, with respect to classical formalisms and model;
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Intelligent prediction and decision support systems are based on signal processing, computer vision (CV), machine learning (ML), software;
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This 2002 book investigates the opportunities in building intelligent decision support systems offered by multi-agent distributed;
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This 2002 book investigates the opportunities in building intelligent decision support systems offered by multi-agent distributed;
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aspects of intelligent decision technologies, from fundamental development to the applied system. It constitutes a great honor and;
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comparative studies, transformation rules, and case diagrams that support all phases of the learner model and the use of Bayesian networks and multi;
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image classification problems using pattern recognition methods, including Artificial Neural Networks (ANN), Support Vector Machines (SVM;
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This is a brand new edition of an essential work on Bayesian networks and decision graphs. It is an introduction to probabilistic graphical;
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practical real-world problem solving and model building, as opposed to algorithms and theory, Risk Assessment and Decision Analysis with Bayesian;
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This book constitutes the refereed proceedings of the First International Conference on Decision Support Systems Technology, ICDSST 2015;
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Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box;
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Artificial Intelligence Tools: Decision Support Systems in Condition Monitoring and Diagnosis discusses various white- and black-box;
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. Understand Bayesian methods including filtering techniques, Bayesian networks, etc., and their use in engineering systems analysis. Learn to;
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, probability, and statistics as needed Establishes the basics of probability, risk, and building and using Bayesian network models, before;
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retrieval of data from visual or multimodal medical databases, disease model-building and clinical decision support systems based on visual or;
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practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition;
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, engineers, scientists and professionals taking part in complex decision processes to successfully implement Bayesian networks, this book equips;
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This book presents innovative and high-quality research regarding advanced decision support systems (DSSs). It describes the foundations;
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This book clearly demonstrates how to best make medical decisions while incorporating clinical practice guidelines and decision support;
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prediction in ruptured brain aneurysms and apply this innovative prognostication model to different areas in medicine. By using Bayesian neural;
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of clustering, classification, summarization, decision making and systems modeling are also addressed. Topics covered in the book include fundamental;
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Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main;
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Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main;
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