Computational Intelligence Processing in Medical Diagnosis

AvManfred Schmitt,Horia-Nicolai Teodorescu

Häftad, Engelska, 2010

Del 96 i serien Studies in Fuzziness and Soft Computing

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2010-10-21
Mått:155 x 235 x 28 mm
Vikt:779 g
Format:Häftad
Språk:Engelska
Serie:Studies in Fuzziness and Soft Computing
Antal sidor:496
Förlag:Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
ISBN:9783790825091

Utforska kategorier

Artificiell intelligens inom Data och IT
Biovetenskap inom Naturvetenskap och teknik
Tillämpad datateknik inom Data och IT

Innehållsförteckning

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.