Using Machine Learning to Identify Patients at Risk of Acquiring HIV in an Urban Health System.

Background: Effective measures exist to prevent the spread of HIV. However, the identification of patients who are candidates for these measures can be a challenge. A machine learning model to predict risk for HIV may enhance patient selection for proactive outreach.