Using electronic health records to identify candidates for human immunodeficiency virus pre‐exposure prophylaxis: An application of super learning to risk prediction when the outcome is rare

Abstract

Machine learning was successful at developing a model to predict 1-year risk of acquiring HIV based on a physician-curated set of predictors extracted from EHRs.