Structure-Leveraged Methods in Breast Cancer Risk Prediction.
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ABSTRACT:
SUBMITTER: Fan J
PROVIDER: S-EPMC5446896 | biostudies-literature | 2016 Dec
REPOSITORIES: biostudies-literature
Publications
Structure-Leveraged Methods in Breast Cancer Risk Prediction.
Fan Jun J Wu Yirong Y Yuan Ming M Page David D Liu Jie J Ong Irene M IM Peissig Peggy P Burnside Elizabeth E
Journal of machine learning research : JMLR 20161201
Predicting breast cancer risk has long been a goal of medical research in the pursuit of precision medicine. The goal of this study is to develop novel penalized methods to improve breast cancer risk prediction by leveraging structure information in electronic health records. We conducted a retrospective case-control study, garnering 49 mammography descriptors and 77 high-frequency/low-penetrance single-nucleotide polymorphisms (SNPs) from an existing personalized medicine data repository. Struc ...[more]
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