A Machine Learning Approach to Predict HIV Viral Load Hotspots in Kenya Using Real-World Data.
Journal:
Health data science
Published Date:
Oct 2, 2023
Abstract
BACKGROUND: Machine learning models are not in routine use for predicting HIV status. Our objective is to describe the development of a machine learning model to predict HIV viral load (VL) hotspots as an early warning system in Kenya, based on routinely collected data by affiliate entities of the Ministry of Health. Based on World Health Organization's recommendations, hotspots are health facilities with ≥20% people living with HIV whose VL is not suppressed. Prediction of VL hotspots provides an early warning system to health administrators to optimize treatment and resources distribution.
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