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Persistent Proxy Discrimination in HIV Testing Prediction Models: A National Fairness Audit of 386,775 US Adults
2026-01-29
health informatics
Title + abstract only
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BackgroundHuman immunodeficiency virus (HIV) disproportionately affects marginalized communities in the United States, with Black Americans comprising 42% of new diagnoses despite representing 13% of the population. Machine learning (ML) prediction models are increasingly deployed for HIV-related decision-making, yet whether they perform equitably across demographic groups remains largely unexamined. MethodsWe conducted a fairness audit using the Behavioral Risk Factor Surveillance System (BRFS...
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