Machine learning key to early detection of acute malnutrition in Sub-Saharan Africa
Published on: May 21, 2025, 6:35 p.m. | Source: Devdiscourse
Among the diverse indicators tested, previous malnutrition outcomes ranked highest in predictive power, followed by sub-county identifiers and satellite-based GPP data. Interestingly, models trained solely on GPP data still outperformed the statistical baseline, demonstrating the power of remotely sensed agricultural indicators in capturing early signals of food insecurity and health risk.
