Loading A Nursing Expert System from Text: A Case Study

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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.

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