  We compare the diagnostic accuracy of three diagnostic inference models: the
simple Bayes model, the multimembership Bayes model, which is isomorphic to the
parallel combination function in the certainty-factor model, and a model that
incorporates the noisy OR-gate interaction. The comparison is done on 20
clinicopathological conference (CPC) cases from the American Journal of
Medicine-challenging cases describing actual patients often with multiple
disorders. We find that the distributions produced by the noisy OR model agree
most closely with the gold-standard diagnoses, although substantial differences
exist between the distributions and the diagnoses. In addition, we find that
the multimembership Bayes model tends to significantly overestimate the
posterior probabilities of diseases, whereas the simple Bayes model tends to
significantly underestimate the posterior probabilities. Our results suggest
that additional work to refine the noisy OR model for internal medicine will be
worthwhile.
