Early malaria risk screening in Nigerian minors using AutoML and cluster-based analysis of non-clinical survey data
It is demonstrated that H2O AutoML provides a robust and automated framework for malaria risk prediction, while cluster-specific modeling further improves predictive performance by accounting for population heterogeneity.