Artificial Neural Networks in Biomedicine

  • Paulo J. G. Lisboa
  • Emmanuel C. Ifeachor
  • Piotr S. Szczepaniak

Part of the Perspectives in Neural Computing book series (PERSPECT.NEURAL)

Table of contents

  1. Front Matter
    Pages i-xiv
  2. Introduction

    1. Paulo J. G. Lisboa, Emmanuel C. Ifeachor, Piotr S. Szczepaniak
      Pages 1-7
  3. Tutorial and Review

    1. Front Matter
      Pages 9-10
    2. William D. Penny, Dirk Husmeier, Stephen J. Roberts
      Pages 11-23
    3. M. F. Jefferson, N. Pendleton, S. B. Lucas
      Pages 39-48
  4. Computer Aided Diagnosis

  5. Signal Processing

    1. Front Matter
      Pages 151-152
    2. Richard Everson, Stephen J. Roberts
      Pages 153-168
    3. Rosaria Silipo, Gustavo Deco, Helmut Bartsch
      Pages 169-180
  6. Image Processing

  7. Back Matter
    Pages 283-287

About this book


Following the intense research activIties of the last decade, artificial neural networks have emerged as one of the most promising new technologies for improving the quality of healthcare. Many successful applications of neural networks to biomedical problems have been reported which demonstrate, convincingly, the distinct benefits of neural networks, although many ofthese have only undergone a limited clinical evaluation. Healthcare providers and developers alike have discovered that medicine and healthcare are fertile areas for neural networks: the problems here require expertise and often involve non-trivial pattern recognition tasks - there are genuine difficulties with conventional methods, and data can be plentiful. The intense research activities in medical neural networks, and allied areas of artificial intelligence, have led to a substantial body of knowledge and the introduction of some neural systems into clinical practice. An aim of this book is to provide a coherent framework for some of the most experienced users and developers of medical neural networks in the world to share their knowledge and expertise with readers.


Elektroenzephalografie Monitor Potential R artificial intelligence artificial neural network biomedical application biomedical applications classification decision support system diagnosis evolution image processing knowledge neural networks

Editors and affiliations

  • Paulo J. G. Lisboa
    • 1
  • Emmanuel C. Ifeachor
    • 2
  • Piotr S. Szczepaniak
    • 3
  1. 1.School of Computing and Mathematical SciencesLiverpool John Moore’s UniversityLiverpoolUK
  2. 2.School of Electronic, Communication and Electrical EngineeringUniversity of PlymouthPlymouthUK
  3. 3.Institute of Computer ScienceTechnical University of LodzLodzPoland

Bibliographic information

  • DOI
  • Copyright Information Springer-Verlag London Limited 2000
  • Publisher Name Springer, London
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-85233-005-7
  • Online ISBN 978-1-4471-0487-2
  • Series Print ISSN 1431-6854
  • Buy this book on publisher's site
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