Title :
System theoretic approach to medical diagnosis
Author :
Nevo, I. ; Guez, A. ; Ahmed, F. ; Roth, J.V.
Author_Institution :
Dept. of Anesthesiology, Albert Einstein Med. Center, Philadelphia, PA, USA
Abstract :
A mathematical model for an adaptive expert system in anesthesia is presented. The concept of clusters that utilize clinical attributes in order to reduce the dimensionality of the patient´s state-space is introduced. One goal of the model is to implement the existing categories and to identify and cluster categories as well as make the system adaptive to new and more optimal categories. Well-known techniques of pattern classification and cluster analysis are used on the measurable dataset to look for new categories or to readjust existing ones. Readjustment is required to optimize the existing categories to give the most efficient classification of the diseases
Keywords :
adaptive systems; computerised pattern recognition; expert systems; mathematical analysis; medical diagnostic computing; adaptive expert system; anesthesia; cluster analysis; disease classification; mathematical model; medical diagnosis; pattern classification; Adaptive systems; Anesthesia; Artificial intelligence; Competitive intelligence; Diagnostic expert systems; Intelligent systems; Mathematical model; Medical diagnosis; Medical treatment; State-space methods;
Conference_Titel :
Computer-Based Medical Systems, 1991. Proceedings of the Fourth Annual IEEE Symposium
Conference_Location :
Baltimore, MD
Print_ISBN :
0-8186-2164-8
DOI :
10.1109/CBMS.1991.128947
