Systematic review of machine learning approaches for predicting sickle cell crisis and mortality risk at the climate-health nexus.

Kama MO, Ajah IA, Ikegwu AC, Obayi AA, Uloko FO, Ogbuagu IC

Open source

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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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

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