Cargando…
Machine learning algorithms for predicting undernutrition among under-five children in Ethiopia
OBJECTIVE: Child undernutrition is a global public health problem with serious implications. In this study, we estimate predictive algorithms for the determinants of childhood stunting by using various machine learning (ML) algorithms. DESIGN: This study draws on data from the Ethiopian Demographic...
Autores principales: | Bitew, Fikrewold H, Sparks, Corey S, Nyarko, Samuel H |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8883776/ https://www.ncbi.nlm.nih.gov/pubmed/34620263 http://dx.doi.org/10.1017/S1368980021004262 |
Ejemplares similares
-
Spatiotemporal Variations and Determinants of Under-Five Stunting in
Ethiopia
por: Bitew, Fikrewold H., et al.
Publicado: (2023) -
Modern contraceptive use and intention to use: implication for under-five mortality in Ethiopia
por: Bitew, Fikrewold, et al.
Publicado: (2019) -
Machine Learning Algorithms for Predicting Stunting among Under-Five Children in Papua New Guinea
por: Shen, Hao, et al.
Publicado: (2023) -
A machine learning classifier approach for identifying the determinants of under-five child undernutrition in Ethiopian administrative zones
por: Fenta, Haile Mekonnen, et al.
Publicado: (2021) -
The epidemiology of undernutrition and its determinants in children under five years in Ghana
por: Boah, Michael, et al.
Publicado: (2019)