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Scientific Computing, Simulation & Modeling - Software Engineering, Artificial Intelligence - General, Neural Networks
Neural Networks and Artificial Intelligence for Biomedical Engineering by Donna L. Hudson,Maurice E. Cohen β€” book cover

Neural Networks and Artificial Intelligence for Biomedical Engineering

by Donna L. Hudson, Maurice E. Cohen
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Overview

Using examples drawn from biomedicine and biomedical engineering, this essential reference book brings you comprehensive coverage of all the major techniques currently available to build computer-assisted decision support systems. You will find practical solutions for biomedicine based on current theory and applications of neural networks, artificial intelligence, and other methods for the development of decision aids, including hybrid systems.

Neural Networks and Artificial Intelligence for Biomedical Engineering offers students and scientists of biomedical engineering, biomedical informatics, and medical artificial intelligence a deeper understanding of the powerful techniques now in use with a wide range of biomedical applications.

Highlighted topics include:

  • Types of neural networks and neural network algorithms
  • Knowledge representation, knowledge acquisition, and reasoning methodologies
  • Chaotic analysis of biomedical time series
  • Genetic algorithms
  • Probability-based systems and fuzzy systems
  • Evaluation and validation of decision support aids.
An Instructor Support FTP site is available from the Wiley editorial department: ftp://ftp.ieee.org/uploads/press/hudson

"...an essential reference offering comprehensive coverage of all the major techniques currently available to build computer-assisted decision support systems...uses examples drawn from biomedicine & biomedical engineering."

About the Author, Donna L. Hudson,Maurice E. Cohen

About the Authors...
Donna L. Hudson is professor of Family and Community Medicine at the University of California, San Francisco (UCSF), and Director of Medical Information Resources at the UCSF Fresno Medical Education Program. She is also a member of the executive committee for the Medical Information Sciences Program at UCSF and a member of the Bioengineering Graduate Group at UC Berkeley and UCSF. In 1987 Dr. Hudson received the Faculty Research Award at UCSF. She has published widely and is coauthor of Comparative Approaches to Medical Reasoning (World Scientific, 1995). She serves as the associate editor for Intelligent Systems for the ISCA International Journal of Computers and Their Applications. Dr. Hudson is a senior member of the Institute of Electrical and Electronics Engineers (IEEE), a member of the Administrative Committee of IEEE Engineering in Medicine and Biology Society, a Fellow of the American Institute of Medical and Biological Engineering, and president of the International Society for Computers and Their Applications.
Maurice E. Cohen is professor of Radiology at the University of California, San Francisco; professor of Mathematics at California State University, Fresno; professor and Founding Member of the Graduate Group in Medical Information Science, and a member of the Bioengineering Graduate Group at UC Berkeley and UCSF. In 1977 Dr. Cohen solved a problem involving Jacobi functions that was believed to be impossible. He received the 1985 American Medical Informatics Association Best Paper Award, the 1991 Outstanding Professor Award at CSUF, and the 1996 Faculty Research Award at UCSF. Dr. Cohen is a Fellow of the American Institute for Medical and Biological Engineering and treasurer of the International Society for Computers and Their Applications. He has published widely and is coauthor of Comparative Approaches to Medical Reasoning (World Scientific, 1995). An accomplished artist, Dr. Cohen provided the cover art for this book. It is an oil painting entitled "Yosemite Vignettes."

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Editorials

Booknews

Hudson (family and community medicine, U. of California) and Cohen (radiology, U. of California) cover a range of topics relevant to computer-assisted techniques for biomedical decision making. Theoretical and practical approaches to the development of neural networks are presented, followed by algorithmic development and application to specific problems. Artificial intelligence applications like knowledge-based acquisition and representation, knowledge-based systems, and searching strategies are looked at and other methodologies, including genetic algorithms, probabilistic systems, fuzzy systems, and hybrid systems are explored. Annotation c. Book News, Inc., Portland, OR (booknews.com)

Book Details

Published
September 24, 1999
Publisher
New York : Institute of Electrical and Electronics Engineers, c2000.
Pages
340
Format
Hardcover
ISBN
9780780334045

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