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Bayesian Network to Predict Breast Cancer Risk of Mammographic Microcalcifications and Reduce Number of Benign Biopsy Results: Initial Experience
Journal Article
Reference:
E. S. Burnside, D. L. Rubin, J. P. Fine, R. Shachter, G. A. Sisney, W. K. Leung. Radiology, 240, 3, 666-673. Published in 2006.
Abstract:

To retrospectively determine whether a Bayesian network (BN) computer model can accurately predict the probability of breast cancer on the basis of risk factors and mammographic appearance of microcalcifications, to improve the positive predictive value (PPV) of biopsy, with pathologic examination and follow-up as reference standards.

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Information last updated: Fri Oct 5 2007
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Stanford School of Medicine