Published on in Vol 14 (2025)
Preprints (earlier versions) of this paper are
available at
https://preprints.jmir.org/preprint/64829, first published
.
Application of Machine Learning and Emerging Health Technologies in the Uptake of HIV Testing: Bibliometric Analysis of Studies Published From 2000 to 2024
Application of Machine Learning and Emerging Health Technologies in the Uptake of HIV Testing: Bibliometric Analysis of Studies Published From 2000 to 2024
Journals
- Jaiteh M, Phalane E, Shiferaw Y, Jallow H, Phaswana-Mafuya R. The Application of Machine Learning Algorithms to Predict HIV Testing Using Evidence from the 2002–2017 South African Adult Population-Based Surveys: An HIV Testing Predictive Model. Tropical Medicine and Infectious Disease 2025;10(6):167 View
- Jaiteh M, Phalane E, Shiferaw Y, Phaswana-Mafuya R. The status of machine learning in HIV testing in South Africa: a qualitative inquiry with stakeholders in Gauteng province. Frontiers in Digital Health 2025;7 View
- Gong X, Yao Y, Wang L, Meng K, Li H. Global burden and forecast of infectious diseases attributable to drug use: evidence from GBD 2021. Frontiers in Public Health 2025;13 View
- Jaiteh M, Phalane E, Shiferaw Y, Phaswana-Mafuya R. Integrating artificial intelligence and machine learning in HIV testing interventions in Gauteng Province, South Africa: Opportunities, challenges, and implementation strategies. Southern African Journal of HIV Medicine 2026;27(1) View
- Bosson-Amedenu S, Mohebujjaman M. Uncertainty‐Aware and Explainable Machine‐Learning Forecasts of Ghana’s Age‐Standardized HIV Incidence Toward 2030. International Journal of Mathematics and Mathematical Sciences 2026;2026(1) View