Development of machine learning algorithms to predict viral load suppression among HIV patients in Conakry (Guinea)

Development of machine learning algorithms to predict viral load suppression among HIV patients in Conakry (Guinea)

BackgroundViral load (VL) suppression is key to ending the global HIV epidemic, and predicting it is critical for healthcare providers and people living with HIV (PLHIV). Traditional research has focused on statistical analysis, but machine learning (ML) is gradually influencing HIV clinical care. W...

Full description

Saved in:
Bibliographic Details
Main Authors: Degninou Yehadji, Geraldine Gray, Carlos Arias Vicente, Petros Isaakidis, Abdourahimi Diallo, Saa Andre Kamano, Thierno Saidou Diallo
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-03-01
Series:Frontiers in Artificial Intelligence
Subjects:
HIV
antiretroviral therapy
viral load
machine learning
prediction
classification
Online Access:https://www.frontiersin.org/articles/10.3389/frai.2025.1446876/full
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://www.frontiersin.org/articles/10.3389/frai.2025.1446876/full

Similar Items