Fuzzy logic-information theory hybrid model for medical diagnostic expert systems

Uncertainty and imprecision is one of the most important problems in medical diagnosis using expert systems: during past decades much research has been directed towards this area. One method, on which this paper is based, is the hybrid model of information theory and fuzzy logic. The information theory is employed in knowledge base acquisition and construction, and fuzzy logic plays the reasoning role. In this research, which is a part of comprehensive project, two parameters are considered for a medical diagnosis. The model consists of knowledge acquisition, knowledge base structure, evaluation, degrees computation and reasoning. This method is applied to the area of oral diseases and a high degree of accuracy in diagnosis has been observed.