Using Machine Learning to Identify Patients at Risk of Acquiring HIV in an Urban Health System
In the peer reviewed Journal of Acquired Immune Deficiency Syndrome (JAIDS), the identification of patients who are at risk for contracting HIV and are candidates for preventative measures is discussed as a machine learning model to predict risk for HIV may enhance patient selection for proactive outreach. This important paper’s authors include PCCI’s Arun Kumar Nethi, MS, Data & Applied Scientist, and Albert Karam, VP, Data Strategy Analytics.
To view the publication, go to: https://journals.lww.com/jaids/fulltext/2024/09010/using_machine_learning_to_identify_patients_at.6.aspx
