Computational Intelligence Processing in Medical Diagnosis
Series: Studies in Fuzziness and Soft Computing; 96;
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Product details:
- Edition number Softcover reprint of hardcover 1st ed. 2002
- Publisher Physica-Verlag HD
- Date of Publication 21 October 2010
- Number of Volumes 1 pieces, Previously published in hardcover
- ISBN 9783790825091
- Binding Paperback
- See also 9783790814637
- No. of pages496 pages
- Size 235x155 mm
- Weight 789 g
- Language English
- Illustrations XX, 496 p. Tables, black & white 0
Categories
Long description:
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.
MoreTable of Contents:
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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