This paper is in the following e-collection/theme issue:

Research Methodology - AI (42) HIV/AIDS/STI Prevention and Care (1053) Machine Learning (2121) Artificial Intelligence (2185) Clinical Information and Decision Making (1953) Health Services in Resource-Poor Settings and LMICs (557) AI Applications in Public Health (32)

Published on in Vol 5 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/68196, first published .
Explainable AI–Driven Comparative Analysis of Machine Learning Models for Predicting HIV Viral Nonsuppression in Ugandan Patients: Retrospective Cross-Sectional Study

Explainable AI–Driven Comparative Analysis of Machine Learning Models for Predicting HIV Viral Nonsuppression in Ugandan Patients: Retrospective Cross-Sectional Study

Explainable AI–Driven Comparative Analysis of Machine Learning Models for Predicting HIV Viral Nonsuppression in Ugandan Patients: Retrospective Cross-Sectional Study

Authors of this article:

Francis Ngema1 Author Orcid Image ;   Albert Whata2 Author Orcid Image ;   Micheal O Olusanya3 Author Orcid Image ;   Siyabonga Mhlongo4 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Francis Ngema   1 * , MBBCh, MADS ;   Albert Whata   2 * , PhD ;   Micheal O Olusanya   3 * , PhD ;   Siyabonga Mhlongo   4 * , PhD

1 Centre of Applied Data Science, University of Johannesburg, Johannesburg, South Africa

2 Department of Statistics, University of Pretoria, Pretoria, South Africa

3 Department of Computer Science and Information Technology, Sol Plaatje University, Kimberley, South Africa

4 Department of Applied Information Systems, University of Johannesburg, Johannesburg, South Africa

*all authors contributed equally

Corresponding Author:

  • Francis Ngema, MBBCh, MADS
  • Centre of Applied Data Science
  • University of Johannesburg
  • Corner Kingsway and University Road
  • Johannesburg 2092
  • South Africa
  • Phone: 27 711822166
  • Email: francisngema@gmail.com