Hybridized artificial intelligence system for reducing neonatal mortality in Nigeria
The hybrid LSTM-ANN model establishes a valuable diagnostic tool for early neonatal disease detection. However, external validation and prospective clinical trials are necessary before clinical deployment.
Authors
- Charity S. Odeyemi
- Bolaji A Omodunbi
- Olatayo Olaniyan (ORCID: https://orcid.org/0000-0002-7349-7500)
- Immanuel Babu Henry Samuel (ORCID: https://orcid.org/0000-0001-7658-9454)
- David B. Olawade (ORCID: https://orcid.org/0000-0003-0188-9836)
- Afeez Adekunle Soladoye (ORCID: https://orcid.org/0000-0002-6349-5173)
Institutions
- University of East London (GB)
- Federal University of Technology (NG)
- Federal Medical Centre (NG)
- Federal Medical Centre (NG)
- Federal University Oye Ekiti (NG)
Publication Details
- Journal
- International Journal of Medical Informatics
- Published
- 2025-10-19
- DOI
- https://doi.org/10.1016/j.ijmedinf.2025.106162
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00