Leveraging Electronic Syndromic Surveillance Synthetic Data to Predict Diarrhoea in Zimbabwean Children Under-Five: An Explainable AI Framework

Machine Learning to Predict Undernutrition in Ghanaian Children under Five Years

Machine Learning to Predict Undernutrition in Ghanaian Children under Five Years

Poster presented at the Deep Learning Indaba 2023 by Eric Komla Anku

An Explainable Stacking Ensemble Model for Predicting Childhood Malnutrition among Under-Five Children in Nigeria

Childhood malnutrition remains a major public health challenge in Nigeria, contributing to child mor

Mobile-based application to predict children under five nutritional status using machine learning techniques

Malnutrition tends to be one of the most important reasons for child mortality in Tanzania and other

PO 8444 CHARACTERISATION OF PATHOGENS CAUSING DIARRHOEA IN CHILDREN UNDER FIVE IN LAMBARÉNÉ, GABON

Background Diarrhoeal disease remains the second leading cause of death in child

From Data to Policy: An AI-Driven Integrated Framework to Predict and Enhance Digital Governance in Beninese Municipalities

Using electronic decision support to enhance provider-caretaker communication for treatment of children under five in Tanzania

One out of every six children in sub-Saharan Africa dies from treatable diseases before reaching age