M. Wayengera

Predicting HIV viral non-suppression in Uganda: development and validation of machine learning and risk stratification models using routine EMR data

Routine EMR data support meaningful, calibrated viral non-suppression risk prediction across a large, multi-site Ugandan HIV program, and both models achieved approximately five-fold enrichment over background prevalence, with clinical utility confirmed by decision curve analysis.