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Applications of AI (379) Artificial Intelligence (2443) Drug Discovery and Clinical Trials (10)

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 (10) Tweetations (2) Metrics

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  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
  6. Boudra T, Idrissou A, Barakat O, Davani S, Valnet Rabier M, Lagoutte-Renosi J. Machine Learning in HIV Care and Antiretroviral Therapy: Systematic Review. Journal of Medical Internet Research 2026;28:e79219 View
  7. Odundo C, Katila C, Njuki S, Onyango L, Makori F. Leveraging Machine Learning Models to Predict HIV/AIDS Treatment Interruption in Patients in Machakos County, Kenya. International Journal of Data Science and Analysis 2025;11(6):158 View
  8. Salami D, Koech E, Turan J, Stafford K, Nyagah L, Ohakanu S, Ngugi A, Charurat M. Prediction of First and Multiple Antiretroviral Therapy Interruptions in People Living With HIV: Comparative Survival Analysis Using Cox and Explainable Machine Learning Models. JMIR Medical Informatics 2026;14:e78964 View
  9. Bashir S, Salad H, Abdullahi Y, Abdi Y, Abdi M, Ahmed N, Saidu Musa S. Artificial intelligence approaches to predicting treatment non-adherence in chronic diseases: a narrative review. Frontiers in Digital Health 2026;8 View
  10. Wu J, Shaw B, Oni B, Jean-Charles K, Dorestan D, Bien-Aime M, Compere-Louis D, Dorce V, Jean-Pierre V, Joseph M, Labbe N. Applying Machine Learning to Predict Loss to Follow-Up Among People Living With HIV in Haiti Using a National Electronic Medical Record Cohort. International Journal of Public Health 2026;71 View