Application of Machine Learning and Emerging Health Technologies in the Uptake of HIV Testing: Bibliometric Analysis of Studies Published From 2000 to 2024
This study identifies trends and hotspots of machine learning and health technology research in relation to HIV testing across various countries, institutions, journals, and authors. The trends are higher in high-income countries with a greater focus on technology applications for HIV self-testing among young people and priority populations. These insights will inform future researchers about the dynamics of research outputs and help them make scholarly decisions to address research gaps in this field.
Authors
- Edith Phalane (ORCID: https://orcid.org/0000-0001-6128-2337)
- Nancy Phaswana‐Mafuya (ORCID: https://orcid.org/0000-0001-9387-0432)
- Yegnanew A. Shiferaw (ORCID: https://orcid.org/0000-0002-2422-4768)
- Hossana Twinomurinzi (ORCID: https://orcid.org/0000-0002-9811-3358)
- Lateef Babatunde Amusa (ORCID: https://orcid.org/0000-0002-8848-1149)
- Musa Jaiteh (ORCID: https://orcid.org/0000-0001-6920-9919)
Institutions
- University of Ilorin (NG)
- University of Johannesburg (ZA)
Publication Details
- Journal
- Interactive Journal of Medical Research
- Published
- 2025-05-22
- DOI
- https://doi.org/10.2196/64829
- Citations
- 3
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.96