Antenatal Iron-Folic Acid Supplementation Gaps in Nigeria: A Predictive Machine Learning Analysis of Non-Initiation and Sub-Optimal Duration Using NDHS 2023–24
- DOI
- 10.64898/2026.09.14.26363020
- Published
- 2026-09-15
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- openRxiv
- Open access
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Cite this work
BibTeX
@article{allodium:10.64898/2026.09.14.26363020,
title = {Antenatal Iron-Folic Acid Supplementation Gaps in Nigeria: A Predictive Machine Learning Analysis of Non-Initiation and Sub-Optimal Duration Using NDHS 2023–24},
author = {Eloghosa Aisosa Nosa-Ihaza and Eze Nnamdi David and Wol Bol Geng Wol and Adeosun Joshua Oluwatimilehin and Uyioghosa Nosayise Nosa-Ihaza},
year = {2026},
doi = {10.64898/2026.09.14.26363020},
url = {https://doi.org/10.64898/2026.09.14.26363020}
}RIS
TY - JOUR TI - Antenatal Iron-Folic Acid Supplementation Gaps in Nigeria: A Predictive Machine Learning Analysis of Non-Initiation and Sub-Optimal Duration Using NDHS 2023–24 AU - Eloghosa Aisosa Nosa-Ihaza AU - Eze Nnamdi David AU - Wol Bol Geng Wol AU - Adeosun Joshua Oluwatimilehin AU - Uyioghosa Nosayise Nosa-Ihaza PY - 2026 DO - 10.64898/2026.09.14.26363020 UR - https://doi.org/10.64898/2026.09.14.26363020 ER -
APA
Nosa-Ihaza, E. A., David, E. N., Wol, W. B. G., Oluwatimilehin, A. J., & Nosa-Ihaza, U. N. (2026). Antenatal Iron-Folic Acid Supplementation Gaps in Nigeria: A Predictive Machine Learning Analysis of Non-Initiation and Sub-Optimal Duration Using NDHS 2023–24. https://doi.org/10.64898/2026.09.14.26363020
Source records
- crossref · retrieved 2026-09-25T10:27:38.309Z