Machine Learning Models for Predicting Malaria in Nigerian Children Under Five

Conference presentation of the IEEE ICTAS 2024 paper. The talk covered the random forest and CatBoost models trained on the 2021 Nigeria Malaria Indicator Survey, the SMOTE treatment of class imbalance, and the household and regional factors the models surface as predictors of malaria in children under five. See the publication for the full abstract and DOI.