This work applies machine learning techniques to climate and health data to predict acute malnutrition risks and support early action, better preparedness, and more targeted nutrition interventions.
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Developing Climate-Informed Machine Learning forecasting tool for acute malnutrition
Presentation at the DHIS2 annual Conference 2026 by Mr. Patrick Omiel, Team Lead Information Systems Support, HISP Uganda