title: Graphical knowledge acquisition for medical diagnostic expert systems.
abstract: Like many textbook authors use text systems for writing their books, expert system authors should have easy to use knowledge acquisition systems for entering and testing their knowledge bases by themselves without much help from 'knowledge engineers'. In this paper, we report on a graphical knowledge acquisition tool (CLASSIKA) based on an expert system shell for heuristic classification (MED2) and designed for direct use by domain experts. We demonstrate how the system has been used for building a rather large expert system for diagnosing rheumatology diseases which is now being tested in clinical use.
authors.affiliation: Universität Karlsruhe, Institut für Logik, Germany.
authors.forename: U
authors.initials: U
authors.lastname: Gappa
authors.forename: F
authors.initials: F
authors.lastname: Puppe
authors.forename: S
authors.initials: S
authors.lastname: Schewe
mesh_terms: D001185:Artificial Intelligence; D003196:Computer Graphics; D003936:Diagnosis, Computer-Assisted; D005103:Expert Systems; D006801:Humans; D007592:Joint Diseases / Q000175:diagnosis; D008838:Microcomputers; D014584:User-Computer Interface