A Bayesian network for mammography Annual Symposium of the American-Medical-Informatics-Association Burnside, E., Rubin, D., Shachter, R. HANLEY & BELFUS INC. 2000: 106–110

Abstract

The interpretation of a mammogram and decisions based on it involve reasoning and management of uncertainty. The wide variation of training and practice among radiologists results in significant variability in screening performance with attendant cost and efficacy consequences. We have created a Bayesian belief network to integrate the findings on a mammogram, based on the standardized lexicon developed for mammography, the Breast Imaging Reporting And Data System (BI-RADS). Our goal in creating this network is to explore the probabilistic underpinnings of this lexicon as well as standardize mammographic decision-making to the level of expert knowledge.

View details for Web of Science ID 000170207500023

View details for PubMedID 11079854