title: Loading a nursing expert system from text: a case study.
abstract: A major bottleneck in the construction of expert systems has traditionally been the solicitation and formalization of expertise from the "human expert." As a means of reducing this bottleneck, the authors propose the use of "text" as a source of knowledge. Acquisition of knowledge from text has not been successful thus far, primarily because most text is not presented in a format (rules, frames, or logic) that can be directly used to load a knowledge base. The authors propose techniques to overcome these inherent problems. This article introduces a model for building an expert system that relies on "text" as the source of knowledge. The model is introduced via a case study involving the building of a nurse expert system designed to replicate the medical diagnostic activities of professional nurses.
authors.affiliation: College of Business Administration, Texas A & M University-Corpus Christi 78412.
authors.forename: W T
authors.initials: WT
authors.lastname: Harding
authors.forename: R T
authors.initials: RT
authors.lastname: Redmond
authors.forename: M C
authors.initials: MC
authors.lastname: Corley
mesh_terms: D001185:Artificial Intelligence; D003198:Computer Simulation; D003199:Computer Systems; D005103:Expert Systems; D006801:Humans; D016294:Models, Nursing; D009733:Nursing Diagnosis