Predictors of mortality among neonates in Lusaka, Zambia: a comparative analysis of machine learning and traditional survival analysis techniques
While traditional Weibull models remain valuable for interpretability, machine learning approaches provide enhanced predictive accuracy. Hybrid modeling strategies may improve early risk identification and inform neonatal care in resource-limited settings.
Authors
- Moleen Zunza (ORCID: https://orcid.org/0000-0002-3270-8439)
- Moses Mukosha (ORCID: https://orcid.org/0000-0002-6079-0564)
- Innocent Maposa (ORCID: https://orcid.org/0000-0002-3448-4096)
- T Mokoena (ORCID: https://orcid.org/0000-0002-3306-5500)
Institutions
- Western Cape Department of Health (ZA)
- Stellenbosch University (ZA)
- University of Zambia (ZM)
Publication Details
- Journal
- Frontiers in Artificial Intelligence
- Published
- 2025-11-11
- DOI
- https://doi.org/10.3389/frai.2025.1606245
- Primary Topic
- Global Maternal and Child Health
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Universiteit Stellenbosch