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Advanced Computational Intelligence Paradigms in Healthcare - 3

Contributor(s): Sordo, Margarita [editor.] | Vaidya, Sachin [editor.] | Jain, Lakhmi C [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Studies in Computational Intelligence: 107Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.Description: X, 257 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783540776628.Subject(s): Engineering | Artificial intelligence | Applied mathematics | Engineering mathematics | Engineering | Appl.Mathematics/Computational Methods of Engineering | Artificial Intelligence (incl. Robotics)DDC classification: 519 Online resources: Click here to access online
Contents:
An Introduction to Computational Intelligence in Healthcare: New Directions -- AI in Clinical Decision Support: Applications in Optical Spectroscopy for Cancer Detection and Diagnosis -- Decision-making Techniques in Ranking of Medicine Effectiveness -- Cognitive Categorizing in UBIAS Intelligent Medical Information Systems -- Intelligent Pervasive Healthcare Systems -- An Agent Middleware for Ubiquitous Computing in Healthcare -- Detection and Classification of Microcalcification Clusters in Mammograms using Evolutionary Neural Networks -- Bayesian Constrained Spectral Method for Segmentation of Noisy Medical Images. Theory and Applications -- Breaking Accessibility Barriers: Computational Intelligence in Music Processing for Blind People -- Ethical Healthcare Agents.
In: Springer eBooksSummary: Advanced Computational Intelligence (CI) paradigms are increasingly used for implementing robust computer applications to foster safety, quality and efficacy in all aspects of healthcare. This research book covers an ample spectrum of the most advanced applications of CI in healthcare. The first chapter introduces the reader to the field of computational intelligence and its applications in healthcare. In the following chapters, readers will gain an understanding of effective CI methodologies in several important topics including clinical decision support, decision making in medicine effectiveness, cognitive categorizing in medical information system as well as intelligent pervasive healthcare systems, and agent middleware for ubiquitous computing. Two chapters are devoted to imaging applications: detection and classification of microcalcifications in mammograms using evolutionary neural networks, and Bayesian methods for segmentation of medical images. The final chapters cover key aspects of healthcare, including computational intelligence in music processing for blind people and ethical healthcare agents. This book will be of interest to postgraduate students, professors and practitioners in the areas of intelligent systems and healthcare.
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E books E books PK Kelkar Library, IIT Kanpur
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An Introduction to Computational Intelligence in Healthcare: New Directions -- AI in Clinical Decision Support: Applications in Optical Spectroscopy for Cancer Detection and Diagnosis -- Decision-making Techniques in Ranking of Medicine Effectiveness -- Cognitive Categorizing in UBIAS Intelligent Medical Information Systems -- Intelligent Pervasive Healthcare Systems -- An Agent Middleware for Ubiquitous Computing in Healthcare -- Detection and Classification of Microcalcification Clusters in Mammograms using Evolutionary Neural Networks -- Bayesian Constrained Spectral Method for Segmentation of Noisy Medical Images. Theory and Applications -- Breaking Accessibility Barriers: Computational Intelligence in Music Processing for Blind People -- Ethical Healthcare Agents.

Advanced Computational Intelligence (CI) paradigms are increasingly used for implementing robust computer applications to foster safety, quality and efficacy in all aspects of healthcare. This research book covers an ample spectrum of the most advanced applications of CI in healthcare. The first chapter introduces the reader to the field of computational intelligence and its applications in healthcare. In the following chapters, readers will gain an understanding of effective CI methodologies in several important topics including clinical decision support, decision making in medicine effectiveness, cognitive categorizing in medical information system as well as intelligent pervasive healthcare systems, and agent middleware for ubiquitous computing. Two chapters are devoted to imaging applications: detection and classification of microcalcifications in mammograms using evolutionary neural networks, and Bayesian methods for segmentation of medical images. The final chapters cover key aspects of healthcare, including computational intelligence in music processing for blind people and ethical healthcare agents. This book will be of interest to postgraduate students, professors and practitioners in the areas of intelligent systems and healthcare.

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