Predicting the Risk of HIV Infection and Sexually Transmitted Diseases Among Men Who Have Sex With Men: Cross-Sectional Study Using Multiple Machine Learning Approaches

Machine learning methods have demonstrated strengths in predicting the risk of HIV infection and STDs among MSM. Risk stratification models and web applications can facilitate clinicians in accurately assessing the risk of infection in individuals with high risk, especially MSM with concealed behaviors, and help them to self-monitor their risk for targeted, timely diagnosis and interventions to reduce new infections.