Computational Intelligence Processing in Medical Diagnosis

• Corporate Author: SpringerLink (Online service)
• Other Authors: Schmitt, Manfred (Editor, http://id.loc.gov/vocabulary/relators/edt), Teodorescu, Horia-Nicolai (Editor, http://id.loc.gov/vocabulary/relators/edt), Jain, Ashlesha (Editor, http://id.loc.gov/vocabulary/relators/edt), Jain, Ajita (Editor, http://id.loc.gov/vocabulary/relators/edt), Jain, Sandhya (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Heidelberg : Physica-Verlag HD : Imprint: Physica, 2002.
• Edition: 1st ed. 2002.
• Series: Studies in Fuzziness and Soft Computing, 96
• Subjects: Health informatics.; Artificial intelligence.; Bioinformatics .; Computational biology .; Health Informatics.; Artificial Intelligence.; Computer Appl. in Life Sciences.

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...

Table 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.