title: Creating an ontology driven rules base for an expert system for medical diagnosis.
abstract: Expert systems of the 1980s have failed on the difficulties of maintaining large rule bases. The current work proposes a method to achieve and maintain rule bases grounded on ontologies (like NCIT). The process described here for an expert system on plasma cell disorder encompasses extraction of a sub-ontology and automatic and comprehensive generation of production rules. The creation of rules is not based directly on classes, but on individuals (instances). Instances can be considered as prototypes of diseases formally defined by "destrictions" in the ontology. Thus, it is possible to use this process to make diagnoses of diseases. The perspectives of this work are considered: the process described with an ontology formalized in OWL1 can be extended by using an ontology in OWL2 and allow reasoning about numerical data in addition to symbolic data.
authors: Unité Inserm U936, IFR 140IFR 140, Faculté de Médecine, University of Rennes 1, France.
authors: Valérie
authors: V
authors: Bertaud Gounot
authors: Valéry
authors: V
authors: Donfack
authors: Jérémy
authors: J
authors: Lasbleiz
authors: Annabel
authors: A
authors: Bourde
authors: Régis
authors: R
authors: Duvauferrier
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003201:Computers; D020000:Decision Support Systems, Clinical / Q000295:instrumentation*; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation* / Q000379:methods; D001330:Electronic Data Processing; D005103:Expert Systems; D006801:Humans; D015233:Models, Statistical; D012984:Software; D018875:Vocabulary, Controlled