Xiang Y, Du J, Fujimoto K, Li F, Schneider J, Tao C. Application of artificial intelligence and machine learning for HIV prevention interventions.
Lancet HIV 2022;
9:e54-e62. [PMID:
34762838 PMCID:
PMC9840899 DOI:
10.1016/s2352-3018(21)00247-2]
[Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Revised: 08/11/2021] [Accepted: 09/02/2021] [Indexed: 01/17/2023]
Abstract
In 2019, the US Government announced its goal to end the HIV epidemic within 10 years, mirroring the initiatives set forth by UNAIDS. Public health prevention interventions are a crucial part of this ambitious goal. However, numerous challenges to this goal exist, including improving HIV awareness, increasing early HIV infection detection, ensuring rapid treatment, optimising resource distribution, and providing efficient prevention services for vulnerable populations. Artificial intelligence has had a pivotal role in revolutionising health care and has shown great potential in developing effective HIV prevention intervention strategies. Although artificial intelligence has been used in a few HIV prevention intervention areas, there are challenges to address and opportunities to explore.
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