Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base — Evaluation of diagnostic performance

Middleton B, Shwe MA, Heckerman DE, Henrion M, Horvitz EJ, Lehmann H, Cooper GF. Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base — Evaluation of diagnostic performance. Methods of Information in Medicine 30 (1991) 256–267.   PMID: 1762579

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

Publication Year: 
1991
Faculty Author: 
Publication Credits: 
Middleton B, Shwe MA, Heckerman DE, Henrion M, Horvitz EJ, Lehmann H, Cooper GF.
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