Abstract
We have developed a probabilistic reformulation of the Quick Medical Reference (QMR)
system. In Part I of this two-part series, we described a two-level, multiply connected
belief-network representation of the QMR knowledge base and a simulation algorithm
to perform probabilistic inference on the reformulated knowledge base. In Part II
of this series, we report on an evaluation of the probabilistic QMR, in which we compare
the performance of QMR to that of our probabilistic system on cases abstracted from
continuing medical education materials from Scientific American Medicine. In addition,
we analyze empirically several components of the probabilistic model and simulation
algorithm.
Key-Words
Evaluation - Expert Systems - Computer-Aided Diagnosis - Probabilistic Inference -
Belief Networks