An ensemble machine learning approach for predicting anemia among under-five children in malaria-endemic sub-Saharan African countries.
- DOI
- 10.1186/s40249-026-01461-6
- Published
- 2026 Jul 13
- Container
- Infectious diseases of poverty
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1186/s40249-026-01461-6,
title = {An ensemble machine learning approach for predicting anemia among under-five children in malaria-endemic sub-Saharan African countries.},
author = {Tekeba B and Baykemagn ND and Mengesha AT and Mengstie MA},
year = {2026},
journal = {Infectious diseases of poverty},
doi = {10.1186/s40249-026-01461-6},
url = {https://doi.org/10.1186/s40249-026-01461-6}
}RIS
TY - JOUR TI - An ensemble machine learning approach for predicting anemia among under-five children in malaria-endemic sub-Saharan African countries. AU - Tekeba B AU - Baykemagn ND AU - Mengesha AT AU - Mengstie MA PY - 2026 JO - Infectious diseases of poverty DO - 10.1186/s40249-026-01461-6 UR - https://doi.org/10.1186/s40249-026-01461-6 ER -
APA
B, T., ND, B., AT, M., & MA, M. (2026). An ensemble machine learning approach for predicting anemia among under-five children in malaria-endemic sub-Saharan African countries.. Infectious diseases of poverty. https://doi.org/10.1186/s40249-026-01461-6
Source records
- pubmed · retrieved 2026-09-25T12:32:51.419Z