Exploring Risk Factors and Predictive Modeling of Child Malnutrition in Pakistan Using Machine Learning
The study highlights the complex interplay of socio-demographic factors in child malnutrition and the potential of machine learning models to effectively predict these conditions, underscoring the need for targeted interventions focusing on maternal education, access to clean water and sanitation, and poverty alleviation, particularly in high-risk regions.
Authors
- Abdul Ghani Khatir
- Muhammad Usman Aslam (ORCID: https://orcid.org/0000-0002-3812-272X)
- Muhammad Usman Saleem (ORCID: https://orcid.org/0009-0002-9480-2399)
- Quanbao Jiang (ORCID: https://orcid.org/0000-0002-1696-7393)
Institutions
- Xi'an Jiaotong University (CN)
- Capital University of Economics and Business (CN)
Publication Details
- Journal
- American Journal of Human Biology
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1002/ajhb.70124
- Citations
- 1
- Primary Topic
- Child Nutrition and Water Access
- Type
- article
- Field-Weighted Citation Impact
- 1.12