Use of machine learning techniques to identify HIV predictors for screening in sub-Saharan Africa

AIM: HIV prevention measures in sub-Saharan Africa are still short of attaining the UNAIDS 90–90-90 fast track targets set in 2014. Identifying predictors for HIV status may facilitate targeted screening interventions that improve health care. We aimed at identifying HIV predictors as well as predic...

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Detalles Bibliográficos
Autores principales: Mutai, Charles K., McSharry, Patrick E., Ngaruye, Innocent, Musabanganji, Edouard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8325403/
https://www.ncbi.nlm.nih.gov/pubmed/34332540
http://dx.doi.org/10.1186/s12874-021-01346-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8325403/
https://www.ncbi.nlm.nih.gov/pubmed/34332540
http://dx.doi.org/10.1186/s12874-021-01346-2

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