The Consistency of the CADIAG-2 Knowledge Base: A Probabilistic Approach

Abstract. The paper presents the methodology and the results of checking consistency of the knowledge base of CADIAG-2, a large-scale medical expert system. Such knowledge base consists of a large collection of rules representing knowledge about various medical entities (symptoms, signs, diseases...) and relationships between them. The major portion of the rules are uncertain, i.e., they specify to what degree a medical entity is confirmed by another medical entity or a combination of them. Given the size of the system and the uncertainty it has been challenging to validate its consistency. Recent attempts to partially formalise CADIAG-2’s knowledge base into decidable G¨odel logics have shown that, on that formalisation, CADIAG-2 is inconsistent. In this paper we verify this result with an alternative, more expressive formalisation of CADIAG-2 as a set of probabilistic conditional statements and apply a state-of-the-art probabilistic logic solver to determine satisfiability of th...

• Type: Journal
• Year: 2010
• Where: LPAR
• Authors: Pavel Klinov, Bijan Parsia, David Picado-Muiño
• Keywords: Automated Reasoning, Knowledge Base, LPAR 2010, Medical, Medical Entity