title: MEDUSA: a fuzzy expert system for medical diagnosis of acute abdominal pain.
abstract: Even today, the diagnosis of acute abdominal pain represents a serious clinical problem. The medical knowledge in this field is characterized by uncertainty, imprecision and vagueness. This situation lends itself especially to be solved by the application of fuzzy logic. A fuzzy logic-based expert system for diagnostic decision support is presented (MEDUSA). The representation and application of uncertain and imprecise knowledge is realized by fuzzy sets and fuzzy relations. The hybrid concept of the system enables the integration of rule-based, heuristic and case-based reasoning on the basis of imprecise information. The central idea of the integration is to use case-based reasoning for the management of special cases, and rule-based reasoning for the representation of normal cases. The heuristic principle is ideally suited for making uncertain, hypothetical inferences on the basis of fuzzy data and fuzzy relations.
authors.affiliation: Department of Computer Science, University of Dortmund, Germany.
authors.forename: M
authors.initials: M
authors.lastname: Fathi-Torbaghan
authors.forename: D
authors.initials: D
authors.lastname: Meyer
mesh_terms: D000006:Abdomen, Acute / Q000209:etiology*; D015746:Abdominal Pain / Q000209:etiology*; D001185:Artificial Intelligence; D003625:Data Collection; D003661:Decision Support Techniques; D003936:Diagnosis, Computer-Assisted; D003937:Diagnosis, Differential; D005103:Expert Systems; D017143:Fuzzy Logic; D006801:Humans; D008487:Medical History Taking; D008491:Medical Informatics Applications