AI Medical Compendium Journal:
AIDS and behavior

Showing 1 to 4 of 4 articles

Qualitative Results from a Pilot Study of an Automated Directly Observed Therapy Intervention Using Artificial Intelligence with Conditional Economic Incentives among Young Adults with HIV.

AIDS and behavior
Digitally monitoring and supporting daily antiretroviral therapy (ART) is a promising strategy for enhanced adherence among young adults with HIV (YWH). We implemented an innovative mobile app-based intervention that included automated directly obser...

The Intersections of COVID-19, HIV, and Race/Ethnicity: Machine Learning Methods to Identify and Model Risk Factors for Severe COVID-19 in a Large U.S. National Dataset.

AIDS and behavior
We investigate risk factors for severe COVID-19 in persons living with HIV (PWH), including among racialized PWH, using the U.S. population-sampled National COVID Cohort Collaborative (N3C) data released from January 1, 2020 to October 10, 2022. We d...

Deep learning for topical trend discovery in online discourse about Pre-Exposure Prophylaxis (PrEP).

AIDS and behavior
Pre-Exposure Prophylaxis (PrEP) interventions are increasingly prevalent on social media. These data can be mined for insights about PrEP that may not be as apparent in surveys including personal musings about PrEP and barriers/facilitators to PrEP u...

Factors Associated with HIV Testing Among Participants from Substance Use Disorder Treatment Programs in the US: A Machine Learning Approach.

AIDS and behavior
HIV testing is the foundation for consolidated HIV treatment and prevention. In this study, we aim to discover the most relevant variables for predicting HIV testing uptake among substance users in substance use disorder treatment programs by applyin...