Predicting Childhood Anaemia in Nigeria: A Machine Learning Approach to Uncover Key Risk Factors
This study shows that machine learning can accurately predict childhood anaemia in Nigeria and identify key risk factors, supporting targeted interventions. Future work should focus on refining models and integrating AI-based interventions to reduce anaemia.
Authors
- Olalekan A. Uthman (ORCID: https://orcid.org/0000-0002-8567-3081)
- Ibrahim Khalil Ja’afar (ORCID: https://orcid.org/0009-0000-9014-868X)
Institutions
- University of Warwick (GB)
- University of Maiduguri (NG)
Publication Details
- Journal
- Public Health Challenges
- Published
- 2025-09-29
- DOI
- https://doi.org/10.1002/puh2.70135
- Citations
- 2
- Primary Topic
- Iron Metabolism and Disorders
- Type
- article
- Field-Weighted Citation Impact
- 3.54