A Machine Learning Health System to Integrate Care for Substance Misuse and HIV Treatment and Prevention Among Hospitalized Patients
This research developed and tested a machine learning classifier using natural language processing to identify hospitalized patients at risk for HIV acquisition or transmission due to substance misuse or high-risk sexual behavior. While the model performed moderately well, gaps in how patient information is documented made accurate risk prediction difficult, highlighting the need for better data and tailored interventions in hospital settings.
