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Neural Networks and Artificial Intelligence for Biomedical Engineering
Contributor(s): Hudson, Donna L. (Author), Cohen, Maurice E. (Author)
ISBN: 0780334043     ISBN-13: 9780780334045
Publisher: Wiley-IEEE Press
OUR PRICE:   $223.20  
Product Type: Hardcover - Other Formats
Published: October 1999
Qty:
Temporarily out of stock - Will ship within 2 to 5 weeks
Annotation: "Using examples drawn from biomedicine and biomedical engineering, this reference text provides 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-making aids, including hybrid systems."--BOOK JACKET.
Additional Information
BISAC Categories:
- Medical | Allied Health Services - Medical Technology
- Computers | Intelligence (ai) & Semantics
- Computers | Neural Networks
Dewey: 610.285
LCCN: 99030757
Series: IEEE Press Biomedical Engineering
Physical Information: 0.89" H x 7.3" W x 10.26" (1.76 lbs) 336 pages
 
Descriptions, Reviews, Etc.
Publisher Description:
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