NEWSWIRE: November 1, 2016
DATELINE: United States of America
Using an automated algorithm to analyze routine electronic health records (EHRs), researchers were able to identify individuals who had an increased risk of HIV and may benefit from pre-exposure prophylaxis (PrEP).
More than 79,000 individuals have taken PrEP over the past 4 years in the United States. The CDC estimates that more than 1.2 million people can still potentially benefit from PrEP, MedPage reported.
During the study, researchers obtained data from the EHRs of Atrius Health, which has about 800,000 patients at 27 sites, and evaluated more than 100 variables. Every newly infected HIV patient, between 2006 and 2015, were matched up with 100 control subjects of the same sex and similar length of Atrius membership who stayed HIV-negative, reported MedPage.
138 HIV cases were identified, of which 13,800 matched controls were chosen for this study. Logistic regression modeling and machine learning were used to predict HIV incident among cases versus the controls.
Logistic regression and computer algorithms were compared to each other and showed there were several machine learning methods successful in predicting incident HIV.
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