Precision HIV Health App, Positive Peers, Powered by Data Harnessing, AI, and Learning

Abstract

Mobile phone applications provide a new and easy-access platform for delivering tailored human immunodeficiency virus (HIV) and sexually transmitted disease (STD) prevention and care. Recent researches have shown that mobile interventions have positive effects in adhesive to care program, antiretroviral therapy (ART), self-management of disease, and are also critical in decreasing the HIV pandemic, and stigmatization. In this paper, a precision health app, Positive Peers (PP), has been developed collaboratively while enabled by data harnessing, Artificial Intelligence (Al), and learning. Positive Peers is an Android/iOS-based social media app for providing support and information to a young adult subgroup living with HIV who are in strong need of support and motivation. We apply an intervention approach combined with Natural Language Processing (NLP) to help the targeted youth to engage more with the app. Using NLP facilitates the flow of information that has a critical role in decreasing the uncertainty of patients by being injected to useful related information. It further improves the interaction of users of the app while providing a compact platform for users to better find the answers to their questions and concerns. The NLP system has been evaluated in an alpha test.