Julgam S. Information technology for analysis and synthesis of system for diagnostics of pathological processes

3. Research object: process of diagnostic decision-making under a priori uncertainty. Research aim: design of intelligent information technology of analysis and synthesis of decision support system (DSS) for pathological processes diagnosis under a priori uncertainty. Research methods: systems analysis, information theory, pattern recognition; information and extreme intelligent technology, object-oriented design. Theoretical and practical results: solved scientific and practical problems of information analysis and synthesis of learning DSS for the diagnosis of pathological processes under a priori uncertainty. Novelty: the method of forming input mathematical description of diagnostic DSS, information and intellectual extreme technology analysis and synthesis of learning DSS operated in cluster analysis and factor input cluster analysis modes, a set of logically related categorical models diagnosis decision support system that operates in cluster analysis and factor input cluster analysis modes are developed, and a modification of Kullback’s information measure in the form of functional of three alternatives accuracy characteristics is proposed and the method of functional evaluating of the effectiveness of learning DSS for diagnosis pathological processes is developed. The degree of implementation: Regional Clinical Infectious Diseases Hospital named. S. J. Krasovytskyi (Sumy), the learning process of the Department of Computer Science of Sumy State University. Scope of application: intelligent information systems diagnosing pathological process in medicine.