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Knowledge-based acquisition of rules for medical diagnosis

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Abstract

Medical consultation systems in the EXPERT framework contain rules written under the guidance of expert physicians. We present a methodology and preliminary implementation of a system that learns compiled rule chains from positive case examples of a diagnostic class and negative examples of alternative diagnostic classes. Rule acquisition is guided by the constraints of physiological process models represented in the system. Evaluation of the system is proceeding in the area of glaucoma diagnosis, and an example of an experiment in this domain is included.

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Authors and Affiliations

  1. From the Department of Computer Science, Rutgers University, 08903, New Brunswick, New Jersey

    George A. Drastal & Casimir A. Kulikowski

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  1. George A. Drastal
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  2. Casimir A. Kulikowski
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Drastal, G.A., Kulikowski, C.A. Knowledge-based acquisition of rules for medical diagnosis. J Med Syst 6, 433–445 (1982). https://doi.org/10.1007/BF00994900

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  • DOI: https://doi.org/10.1007/BF00994900

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