title: Comparison of three Knowledge Representation formalisms for encoding the NCEP Cholesterol Guidelines.
abstract: Although many Knowledge Representation (KR) formalisms have been used to encode care guidelines, there are few direct comparisons among different formalisms. In order to compare their suitability for encoding care guidelines, three different KR formalisms were used to encode the National Cholesterol Education Panel (NCEP) guideline. PROLOG, a First Order Logic system, CLASSIC, a frame-based representation system, and CLIPS, a production rule system, were used in the comparison. All three representations allowed accurate encoding of the guideline. PROLOG produced the most compact representation, but proved the most difficult to debug. The lack of arbitrary disjunction in CLASSIC greatly increased the complexity of the encoding. Overall, the CLIPS representation was the most intuitive and easiest to use.
authors.affiliation: Center for Medical Informatics, Columbia University College of Physicians and Surgeons, New York, New York 10032.
authors.forename: J
authors.initials: J
authors.lastname: Starren
authors.forename: G
authors.initials: G
authors.lastname: Xie
mesh_terms: D001185:Artificial Intelligence; D002784:Cholesterol / Q000097:blood; D005103:Expert Systems; D006937:Hypercholesterolemia / Q000175:diagnosis / Q000628:therapy*; D017410:Practice Guidelines as Topic; D011381:Programming Languages
chemical_list: D002784:Cholesterol