Applying machine learning and predictive modeling to retention and viral suppression in South African HIV treatment cohorts

HIV treatment programs face challenges in identifying patients at risk for loss-to-follow-up and uncontrolled viremia. We applied predictive machine learning algorithms to anonymised, patient-level HIV programmatic data from two districts in South Africa, 2016–2018. We developed patient risk scores...

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Detalles Bibliográficos
Autores principales: Maskew, Mhairi, Sharpey-Schafer, Kieran, De Voux, Lucien, Crompton, Thomas, Bor, Jacob, Rennick, Marcus, Chirowodza, Admire, Miot, Jacqui, Molefi, Seithati, Onaga, Chuka, Majuba, Pappie, Sanne, Ian, Pisa, Pedro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9325703/
https://www.ncbi.nlm.nih.gov/pubmed/35882962
http://dx.doi.org/10.1038/s41598-022-16062-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9325703/
https://www.ncbi.nlm.nih.gov/pubmed/35882962
http://dx.doi.org/10.1038/s41598-022-16062-0

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