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

Applications of AI (246) Artificial Intelligence (1996) Drug Discovery and Clinical Trials (5)

Published on in Vol 2 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/44432, first published .
Predicting Treatment Interruption Among People Living With HIV in Nigeria: Machine Learning Approach

Predicting Treatment Interruption Among People Living With HIV in Nigeria: Machine Learning Approach

Predicting Treatment Interruption Among People Living With HIV in Nigeria: Machine Learning Approach

Authors of this article:

Matthew-David Ogbechie1 Author Orcid Image ;   Christa Fischer Walker2 Author Orcid Image ;   Mu-Tien Lee3 Author Orcid Image ;   Amina Abba Gana1 Author Orcid Image ;   Abimbola Oduola1 Author Orcid Image ;   Augustine Idemudia1 Author Orcid Image ;   Matthew Edor1 Author Orcid Image ;   Emily Lark Harris4 Author Orcid Image ;   Jessica Stephens5 Author Orcid Image ;   Xiaoming Gao3 Author Orcid Image ;   Pai-Lien Chen3 Author Orcid Image ;   Navindra Etwaroo Persaud2 Author Orcid Image
Article Authors Cited by (5) Tweetations (2) Metrics

Journals

  1. Nkengasong J, Bunnell R, Nandakumar A, Katz I, Sanhokwe H, Reid M. PEPFAR's mission. The Lancet 2024;404(10469):2226 View
  2. Ijaiya M, Troncoso E, Mutloatse M, Ifeanyi D, Obasa B, Emerenini F, De Voux L, Mnguni T, Parrott S, Okwor E, Dare B, Ogundare O, Atuma E, Strachan M, Fayorsey R, Curran K, Hessam S. Use of machine learning in predicting continuity of HIV treatment in selected Nigerian States. PLOS Global Public Health 2025;5(4):e0004497 View
  3. Maskew M, Parrott S, De Voux L, Sharpey-Schafer K, Crompton T, Govender A, Pisa P, Rosen S. Triaging Clients at Risk of Disengagement from HIV Care: Application of a Predictive Model to Clinical Trial Data in South Africa. Risk Management and Healthcare Policy 2025;Volume 18:1601 View
  4. Yeneakal K, Teferi G, Mihret T, Mengistu A, Tizie S, Tadele M. Predicting antiretroviral therapy adherence status of adult HIV-positive patients using machine-learning Northwest, Ethiopia, 2025. BMC Medical Informatics and Decision Making 2025;25(1) View
  5. Kwarah W, Vroom F, Dwomoh D, Bosomprah S. Evaluating predictive performance, validity, and applicability of machine learning models for predicting HIV treatment interruption: a systematic review. BMC Global and Public Health 2025;3(1) View