Comparative Analysis of Machine Learning Algorithms for Predicting Under-Five Mortality: Evidence from Tanzania Demographic and Health Survey

Machine learning approach for predicting under-five mortality determinants in Ethiopia: evidence from the 2016 Ethiopian Demographic and Health Survey

Abstract There is a dearth of literature on the use of machine learning models to predict important

Comparative analysis of machine learning algorithms for predicting diarrhea among under-five children in Ethiopia: Evidence from 2016 EDHS

Background: Diarrhea is a major cause of mortality and morbidity in under-5 children globally, espec

Determinants of Under-Five Mortality in Ghana: Evidence from the Ghana Demographic and Health Survey

Background and Objectives: This study aims to investigate the strength of the

Optimizing machine learning models for predicting anemia among under-five children in Ethiopia: insights from Ethiopian demographic and health survey data

Machine learning algorithms for predicting undernutrition among under-five children in Ethiopia

Abstract Objective: Child undernutrition is a global public health problem with s

Predictive models and under-five mortality determinants in Ethiopia: evidence from the 2016 Ethiopian Demographic and Health Survey

Abstract Background There is a dearth of literature on predictive models estimating under-