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Computational Intelligence Processing in Medical Diagnosis

Computational Intelligence Processing in Medical Diagnosis
United States of America

Was R2,576.95
Now R2,319.26
(eB 23193)

Delivery time: Usually within 10 working days.


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Format: Hardcover
Editor: Manfred Schmitt; Ajita Jain; Ashlesha Jain; Sandhya Jain; L.C. Jain; H-.N. Teodorescu
Publisher: Springer Berlin Heidelberg
ISBN: 9783790814637
Publication date: January 2002
Length: 238mm
Width: 160mm
Thickness: 34mm
Weight: 880g
Pages: 496
Illustrations: Illustrated
Readership: Professional & scholarly
Buy this product
Computational Intelligence Processing in Medical Diagnosis
Author: Manfred Schmitt; Horia-Nicolai Teodorescu

Was R2,576.95

Now R2,319.26

 


This volume presents advanced applications of machine intelligence in medicine and bio-medical engineering. Applied methods include knowledge bases, expert systems, neural networks, neuro-fuzzy systems, evolvable systems, wavelet transforms and specific internet applications.

Computational intelligence techniques are gaining momentum in the medical prognosis and diagnosis. This volume presents advanced applications of machine intelligence in medicine and bio-medical engineering. Applied methods include knowledge bases, expert systems, neural networks, neuro-fuzzy systems, evolvable systems, wavelet transforms, and specific internet applications. The volume is written in view of explaining to the practitioner the fundamental issues related to computational intelligence paradigms and to offer a fast and friendly-managed introduction to the most recent methods based on computer intelligence in medicine.

  • Introduction * Computational intelligence techniques in medical decision making
  • the data mining perspective * Internet
  • based decision support for evidence
  • based medicine * Integrating kernel methods into a knowledge
  • based approach to evidence
  • based medicine * Case
  • based reasoning prognosis for temporal courses * Pattern recognition in intensive care online monitoring * Artificial neural network models for timely assessment of trauma complication risk * Artificial neural networks in medical diagnosis * The application of neural networks in the classification of the electrocardiogram * Neural network predictions of significant coronary artery stenosis in women * A modular neural network system for the analysis of nuclei in histopathological sections * Septic shock diagnosis by neural networks and rule based systems * Monitoring depth of anesthesia * Combining evolutionary and fuzzy techniques in medical diagnosis * Genetic algorithms for feature selection in computer
  • aided diagnosis


 
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