A Bayesian network for mammography

  title={A Bayesian network for mammography},
  author={Elizabeth S. Burnside and Daniel L. Rubin and Ross D. Shachter},
  journal={Proceedings. AMIA Symposium},
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… CONTINUE READING

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