Are normative expert systems appropriate for diagnostic pathology?

Abstract

Conceptual models for diagnostic reasoning proposed in the medical literature are presented to stimulate discussion about the issue of the appropriateness of probabilistic knowledge-based systems for medical diagnosis. Evidence is presented to corroborate the authors' view that diagnosis is a problem-solving task, rather than a decision-making task. In the authors' opinion, probabilistic reasoning is better suited to situations dealing with choices for clinical intervention, rather than to those dealing with determining the correct diagnosis. A critique is given of a diagnostic Bayesian expert system for lymph node pathology. In empirical studies, diagnostic Bayesian systems have been shown to typically list the correct diagnosis as the program's first choice 60% to 70% of the time. One reason for this undistinguished level of diagnostic performance is that Bayesian systems are not designed to represent and use knowledge the same way that an expert does.