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The (Probabilistic) Logical Content of Cadiag2 - Rule-based Probabilistic Approach

Cadiag2 is a well-known rule-based expert system that aims at providing support for medical diagnose in internal medicine. Cadiag2 consists of a knowledge base in the form of a set of if-then rules that relate medical entities, in this paper interpreted as conditional probabilistic statements, and an inference engine constructed upon methods of fuzzy set theory. The aim underlying this paper is the understanding of the inference in Cadiag2. To that purpose we provide a (probabilistic) logical formalisation of the inference of the system and check its adequacy with probability theory.