Identifying determinants of under-5 mortality in Bangladesh: A machine learning approach with BDHS 2022 data

The Random Forest model excelled in predicting under-5 mortality in Bangladesh identifying key predictors such as household size, wealth, parental education, ANC visits, birth order and father's occupation. These findings underscore the efficacy of machine learning in predicting under-5 mortality and identifying critical determinants these also provide a data-driven foundation for policymakers to design targeted interventions, such as improving access to maternal healthcare, promoting parental education and addressing socio-economic inequalities, ultimately contributing to enhanced child survival outcomes in Bangladesh.