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

• Main Authors: Stephanie D. Roche (Author), Obinna I. Ekwunife (Author), Rouella Mendonca (Author), Benn Kwach (Author), Victor Omollo (Author), Shengruo Zhang (Author), Patricia Ongwen (Author), David Hattery (Author), Sam Smedinghoff (Author), Sarah Morris (Author), Daniel Were (Author), Dino Rech (Author), Elizabeth A. Bukusi (Author), Katrina F. Ortblad (Author)
• Format: Book
• Published: Frontiers Media S.A., 2024-02-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

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...