Machine learning prediction of kangaroo mother care in Sierra Leone: a comparative study of feature selection techniques and classification algorithms
Machine learning models, particularly ensemble methods combined with comprehensive feature selection techniques, demonstrate strong predictive capability for KMC practice, offering valuable insights for maternal and child health interventions in Sierra Leone.
Authors
- Ojima Zechariah Wada (ORCID: https://orcid.org/0000-0002-8328-3557)
- Ademola Ezekiel Adekoya (ORCID: https://orcid.org/0009-0006-6275-9030)
- Augustus Osborne (ORCID: https://orcid.org/0000-0002-0226-841X)
- David B. Olawade (ORCID: https://orcid.org/0000-0003-0188-9836)
- Afeez A Soladoye
- Kobloobase O Usani (ORCID: https://orcid.org/0009-0009-9668-3128)
Institutions
- University of Gloucestershire (GB)
- Birmingham City University (GB)
- University of Ibadan (NG)
- Adeleke University (NG)
- Arden University (GB)
- Hamad bin Khalifa University (QA)
- Sierra Leone Urban Research Centre (SL)
- Sierra Leone Agricultural Research Institute (SL)
- Federal University Oye Ekiti (NG)
Publication Details
- Journal
- International Journal of Medical Informatics
- Published
- 2025-10-26
- DOI
- https://doi.org/10.1016/j.ijmedinf.2025.106166
- Primary Topic
- Virology and Viral Diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.00