A probabilistic interpretation of the medical expert system CADIAG-2

Abstract

CADIAG-2 is a well-known expert system aimed at providing support for medical diagnose in the field of internal medicine. CADIAG-2 consists of a knowledge base in the form of a set of IF-THEN rules that relate distinct 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 logical structure of the inference in CADIAG-2. To that purpose, we provide a (probabilistic) logical formalisation of the inference of the system and check its adequacy with probabilistic logic.