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Pre-Exposure Prophylaxis

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Constrained binary classification using ensemble learning: an application to cost-efficient targeted PrEP strategies.

Statistics in medicine
Binary classification problems are ubiquitous in health and social sciences. In many cases, one wishes to balance two competing optimality considerations for a binary classifier. For instance, in resource-limited settings, an human immunodeficiency v...

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...

"What Did You Say, ChatGPT?" The Use of AI in Black Women's HIV Self-Education: An Inductive Qualitative Data Analysis.

The Journal of the Association of Nurses in AIDS Care : JANAC
The emergence of widely accessible artificial intelligence (AI) chatbots such as ChatGPT presents unique opportunities and challenges in public health self-education. This study examined simulations with ChatGPT for its use in public education of sex...

Improving HIV preexposure prophylaxis uptake with artificial intelligence and automation: a systematic review.

AIDS (London, England)
OBJECTIVES: To identify studies promoting the use of artificial intelligence (AI) or automation with HIV preexposure prophylaxis (PrEP) care and explore ways for AI to be used in PrEP interventions.

Ameliorating Racial Disparities in HIV Prevention via a Nurse-Led, AI-Enhanced Program for Pre-Exposure Prophylaxis Utilization Among Black Cisgender Women: Protocol for a Mixed Methods Study.

JMIR research protocols
BACKGROUND: HIV pre-exposure prophylaxis (PrEP) is a critical biomedical strategy to prevent HIV transmission among cisgender women. Despite its proven effectiveness, Black cisgender women remain significantly underrepresented throughout the PrEP car...