Tuesday, June 1, 2021

Fuzzy and Neuro-Fuzzy Systems in Medicine

Fuzzy and Neuro-Fuzzy Systems in Medicine PDF
By:Horia-Nicolai L Teodorescu,Abraham Kandel,Lakhmi C. Jain
Published on 1998-09-30 by CRC Press

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Fuzzy and Neuro-Fuzzy Systems in Medicineprovides a thorough review of state-of-the-art techniques and practices, defines and explains relevant problems, as well as provides solutions to these problems. After an introduction, the book progresses from one topic to another - with a linear development from fundamentals to applications. Chapters discuss: a historical perspective of fuzzy systems technology and neuro-fuzzy systems technology in medicine and biology the relationship of fuzzy logic to the human brain analysis and classification of signals using fuzzy, neuro-fuzzy, and wavelet methods wavelet analysis combined with neuro-fuzzy systems in contouring gated SPECT images of ventricles a detailed application based on a knowledge-based system that uses fuzzy techniques, multispectral analysis, and image processing algorithms applications in the field of dentistry a dedicated system for myocardial ischemia diagnosis a typical expert system used in intensive care units designing and tuning fuzzy rules for medical diagnosis knowledge processing, decision-making, and control strategies combined with control methods in medical equipment current technological problems and trends in the neural and fuzzy hardware implementation field The well-balanced chapters cover all the major fields in medicine and biomedical engineering, including imaging, prosthetics, psychology, medical equipment, diagnosis, and treatment.

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Book which was published by CRC Press since 1998-09-30 have ISBNs, ISBN 13 Code is 9780849398063 and ISBN 10 Code is 0849398061

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Clinical Decision Support Systems

Clinical Decision Support Systems PDF
By:Eta S. Berner
Published on 2013-06-29 by Springer Science & Business Media

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Written by nationally and internationally recognised experts on the design, evaluation and application of such systems, this book examines the impact of practitioner and patient use of computer-based diagnostic tools. It serves simultaneously as a resource book on diagnostic systems for informatics specialists; a textbook for teachers or students in health or medical informatics training programs; and as a comprehensive introduction for clinicians, with or without expertise in the applications of computers in medicine, who are interested in learning about current developments in computer-based diagnostic systems. Designed for a broad range of clinicians in need of decision support.

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Book which was published by Springer Science & Business Media since 2013-06-29 have ISBNs, ISBN 13 Code is 9781475739039 and ISBN 10 Code is 1475739036

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Introduction to Computers for Healthcare Professionals

Introduction to Computers for Healthcare Professionals PDF
By:Irene Joos,Nancy Whitman,Marjorie Smith
Published on 2005 by Jones & Bartlett Learning

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The only computer and information literacy book designed specifically for students in health care disciplines, Introduction to Computers for Healthcare Professionals, Fourth Edition explains hardware, popular software programs, operating systems, research applications, and computer-assisted communication, including sections on information access, evaluation and use, and the Internet. Built on the Computers in Small Bytes Foundation, the revised Fourth Edition continues to present this information with great detail and clarity, featuring the most recent MS Office programs, and focusing on the security of systems and data.

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Annual Report of the Secretary of the Navy

Annual Report of the Secretary of the Navy PDF
By:United States. Navy Department
Published on 1918 by

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Official Records of the World Health Organization

Official Records of the World Health Organization PDF
By:Interim Commission of the World Health Organization
Published on 1974 by

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Modeling and Inverse Problems in the Presence of Uncertainty

Modeling and Inverse Problems in the Presence of Uncertainty PDF
By:H. T. Banks,Shuhua Hu,W. Clayton Thompson
Published on 2014-04-01 by CRC Press

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Modeling and Inverse Problems in the Presence of Uncertainty collects recent research—including the authors’ own substantial projects—on uncertainty propagation and quantification. It covers two sources of uncertainty: where uncertainty is present primarily due to measurement errors and where uncertainty is present due to the modeling formulation itself. After a useful review of relevant probability and statistical concepts, the book summarizes mathematical and statistical aspects of inverse problem methodology, including ordinary, weighted, and generalized least-squares formulations. It then discusses asymptotic theories, bootstrapping, and issues related to the evaluation of correctness of assumed form of statistical models. The authors go on to present methods for evaluating and comparing the validity of appropriateness of a collection of models for describing a given data set, including statistically based model selection and comparison techniques. They also explore recent results on the estimation of probability distributions when they are embedded in complex mathematical models and only aggregate (not individual) data are available. In addition, they briefly discuss the optimal design of experiments in support of inverse problems for given models. The book concludes with a focus on uncertainty in model formulation itself, covering the general relationship of differential equations driven by white noise and the ones driven by colored noise in terms of their resulting probability density functions. It also deals with questions related to the appropriateness of discrete versus continuum models in transitions from small to large numbers of individuals. With many examples throughout addressing problems in physics, biology, and other areas, this book is intended for applied mathematicians interested in deterministic and/or stochastic models and their interactions. It is also suitable for scientists in biology, medicine, engineering, and physics working on basic modeling and inverse problems, uncertainty in modeling, propagation of uncertainty, and statistical modeling.

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