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Measuring the performance of computer vision artificial intelligence to interpret images of HIV self-testing results

IntroductionHIV self-testing (HIVST) is highly sensitive and specific, addresses known barriers to HIV testing (such as stigma), and is recommended by the World Health Organization as a testing option for the delivery of HIV pre-exposure prophylaxis (PrEP). Nevertheless, HIVST remains underutilized...

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Principais autores: Stephanie D. Roche, Obinna I. Ekwunife, Rouella Mendonca, Benn Kwach, Victor Omollo, Shengruo Zhang, Patricia Ongwen, David Hattery, Sam Smedinghoff, Sarah Morris, Daniel Were, Dino Rech, Elizabeth A. Bukusi, Katrina F. Ortblad
Formato: Artigo
Idioma:Inglês
Publicado em: Frontiers Media S.A. 2024-02-01
coleção:Frontiers in Public Health
Assuntos:
artificial intelligence
HIV self-testing
HIV prevention
mHealth
sub-Saharan Africa
differentiated service delivery
Acesso em linha:https://www.frontiersin.org/articles/10.3389/fpubh.2024.1334881/full
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