title: A diagnostic expert system for colonic lesions.
abstract: The diagnostic expert system for colonic lesions (DESCL) was designed to discriminate colonic adenoma and adenocarcinoma from normal colonic tissue. Although it was originally developed for use in conjunction with a machine vision analytic system, the DESCL has evolved into a teaching tool and a model for conceptual machine learning. The expert system is table driven and consists of a shell and a knowledge base. The latter comprises a series of architectural and cytologic observations and a quantitative estimate of diagnostic importance relating these observations to diagnostic outcome. In a validation study of 100 colonic lesions, the expert system achieved a success rate of 98%. It has the flexibility to allow individual pathologists to "customize" the knowledge base to suit their diagnostic criteria.
authors.affiliation: Department of Pathology, University of Arizona Health Sciences Center, Tucson 85724.
authors.forename: A R
authors.initials: AR
authors.lastname: Graham
authors.forename: S H
authors.initials: SH
authors.lastname: Paplanus
authors.forename: P H
authors.initials: PH
authors.lastname: Bartels
mesh_terms: D000230:Adenocarcinoma / Q000175:diagnosis*; D000236:Adenoma / Q000175:diagnosis*; D003110:Colonic Neoplasms / Q000175:diagnosis*; D003936:Diagnosis, Computer-Assisted; D005103:Expert Systems; D006801:Humans