Inference in the Promedas Medical Expert System

Authors:
Bastian Wemmenhove;Joris M. Mooij;Wim Wiegerinck;Martijn Leisink;Hilbert J. Kappen;Jan P. Neijt
Affiliations:
Department of Biophysics, Radboud University Nijmegen, 6525 EZ Nijmegen, The Netherlands;Department of Biophysics, Radboud University Nijmegen, 6525 EZ Nijmegen, The Netherlands;Department of Biophysics, Radboud University Nijmegen, 6525 EZ Nijmegen, The Netherlands;Department of Biophysics, Radboud University Nijmegen, 6525 EZ Nijmegen, The Netherlands;Department of Biophysics, Radboud University Nijmegen, 6525 EZ Nijmegen, The Netherlands;Internal Medicine, University Hospital Utrecht Utrecht, The Netherlands
Venue:
AIME '07 Proceedings of the 11th conference on Artificial Intelligence in Medicine
Year:
2007

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Abstract

In the current paper, the Promedas model for internal medicine, developed by our team, is introduced. The model is based on up-to-date medical knowledge and consists of approximately 2000 diagnoses, 1000 findings and 8600 connections between diagnoses and findings, covering a large part of internal medicine. We show that Belief Propagation (BP) can be successfully applied as approximate inference algorithm in the Promedas network. In some cases, however, we find errors that are too large for this application. We apply a recently developed method that improves the BP results by means of a loop expansion scheme. This method, termed Loop Corrected (LC) BP, is able to improve the marginal probabilities significantly, leaving a remaining error which is acceptable for the purpose of medical diagnosis.