Name: Computational Intelligence Processing in Medical Diagnosis
Price: 1069.68 RON
Availability: OnlineOnly
Author: Manfred Schmitt
ISBN: 9783790814637

Computational Intelligence Processing in Medical Diagnosis: Studies in Fuzziness and Soft Computing, cartea 96

Manfred Schmitt

Horia-Nicolai Teodorescu

Ashlesha Jain

Ajita Jain

Sandhya Jain

en Limba Engleză Paperback – 21 oct 2010

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.

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Specificații

ISBN-13: 9783790825091
ISBN-10: 3790825093
Pagini: 520
Ilustrații: XX, 496 p.
Dimensiuni: 155 x 235 x 28 mm
Greutate: 0.78 kg
Ediția:Softcover reprint of hardcover 1st ed. 2002
Editura: Physica
Colecția Studies in Fuzziness and Soft Computing
Seria Studies in Fuzziness and Soft Computing

Locul publicării:Heidelberg, Germany

Cuprins

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.