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An Integrated Approach to Learning Bayesian Networks of Rules.

, , , , and . ECML, volume 3720 of Lecture Notes in Computer Science, page 84-95. Springer, (2005)

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Validation of Results from Knowledge Discovery: Mass Density as a Predictor of Breast Cancer., , , , , and . J. Digital Imaging, 23 (5): 554-561 (2010)A collective ranking method for genome-wide association studies., , , and . BCB, page 313-320. ACM, (2012)Improving breast cancer risk prediction by using demographic risk factors, abnormality features on mammograms and genetic variants., , , , , , , , , and . AMIA, AMIA, (2018)Optimal Breast Biopsy Decision-Making Based on Mammographic Features and Demographic Factors., , and . Operations Research, 58 (6): 1577-1591 (2010)Boosting First-Order Clauses for Large, Skewed Data Sets., , and . ILP, volume 5989 of Lecture Notes in Computer Science, page 166-177. Springer, (2009)High-Dimensional Structured Feature Screening Using Binary Markov Random Fields., , , , , and . AISTATS, volume 22 of JMLR Proceedings, page 712-721. JMLR.org, (2012)View Learning for Statistical Relational Learning: With an Application to Mammography., , , , , , and . IJCAI, page 677-683. Professional Book Center, (2005)Comparison of screening full-field digital mammography and digital breast tomosynthesis technical recalls., , , , , and . IWBI, volume 10718 of SPIE Proceedings, page 1071820. SPIE, (2018)Predicting malignancy from mammography findings and image-guided core biopsies., , , , and . IJDMB, 11 (3): 257-276 (2015)Support Vector Machines for Differential Prediction., , , , , and . ECML/PKDD (2), volume 8725 of Lecture Notes in Computer Science, page 50-65. Springer, (2014)