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Article

Semi-Supervised Learning of the Electronic Health Record for Phenotype Stratification

2016-02-18

Abstract excerpt

Patient interactions with health care providers result in entries to electronic health records (EHRs). EHRs were built for clinical and billing purposes but contain many data points about an individual. Mining these records provides opportunities to extract electronic phenotypes, which can be paired with genetic data to identify genes underlying common human diseases. This task remains challenging: high quality ph...

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Literature Corpus work
a1f51f61-1dcd-51e0-8fd0-14920b5edef3
DOI
10.1101/039800
Open publication

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Semi-Supervised Learning of the Electronic Health Record for Phenotype StratificationDOI 10.1101/039800
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