Systematic review of machine learning approaches for predicting sickle cell crisis and mortality risk at the climate-health nexus.
- DOI
- 10.1186/s12911-026-03796-4
- Published
- 2026 Sep 3
- Container
- BMC medical informatics and decision making
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1186/s12911-026-03796-4,
title = {Systematic review of machine learning approaches for predicting sickle cell crisis and mortality risk at the climate-health nexus.},
author = {Kama MO and Ajah IA and Ikegwu AC and Obayi AA and Uloko FO and Ogbuagu IC},
year = {2026},
journal = {BMC medical informatics and decision making},
doi = {10.1186/s12911-026-03796-4},
url = {https://doi.org/10.1186/s12911-026-03796-4}
}RIS
TY - JOUR TI - Systematic review of machine learning approaches for predicting sickle cell crisis and mortality risk at the climate-health nexus. AU - Kama MO AU - Ajah IA AU - Ikegwu AC AU - Obayi AA AU - Uloko FO AU - Ogbuagu IC PY - 2026 JO - BMC medical informatics and decision making DO - 10.1186/s12911-026-03796-4 UR - https://doi.org/10.1186/s12911-026-03796-4 ER -
APA
MO, K., IA, A., AC, I., AA, O., FO, U., & IC, O. (2026). Systematic review of machine learning approaches for predicting sickle cell crisis and mortality risk at the climate-health nexus.. BMC medical informatics and decision making. https://doi.org/10.1186/s12911-026-03796-4
Source records
- pubmed · retrieved 2026-09-25T14:43:37.259Z