A multidisciplinary team of researchers has developed an artificial intelligence (AI) model that can predict acute child malnutrition in Kenya up to six months in advance. The tool offers governments and humanitarian organizations critical lead time to deliver life-saving food, health care, and supplies to at-risk areas. The machine learning model outperforms traditional approaches by integrating clinical data from more than 17,000 Kenyan health facilities with satellite data on crop health and productivity. It achieves 89% accuracy when forecasting one month out and maintains 86% accuracy over six months — a significant improvement over simpler baseline models that rely only on recent historical child malnutrition prevalence trends.
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