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Sankore

Named after the University of Sankore in Timbuktu — one of the world’s oldest centres of learning. Every figure here is computed from work-level records in our own graph, never copied from a source’s summary count.

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Hybridized artificial intelligence system for reducing neonatal mortality in Nigeria

2025International Journal of Medical InformaticsJournalOpen access

10.1016/j.ijmedinf.2025.106162 Full text0 citations

Authors

6 authors across 5 institutions in 2 countries.

Charity S. OdeyemiFirst author
- Federal University Oye Ekiti (NG)
- Federal University of Technology (NG)
Olatayo Moses Olaniyan
- Federal University Oye Ekiti (NG)
as printed: Olatayo M. Olaniyan
Bolaji A. Omodunbi
- Federal University Oye Ekiti (NG)
Ibitoye B. Samuel
- Federal Medical Centre (NG)
- Federal Medical Centre (NG)
Afeez Adekunle Soladoye
- Federal University Oye Ekiti (NG)
as printed: Afeez A. Soladoye
David B. OlawadeSenior authorCorresponding

Fields

Assignment is probabilistic — a work belongs to several fields in proportions.

Neonatal and Maternal Infectionslevel 3 · 0.48
Preterm Birth and Chorioamnionitislevel 3 · 0.10
Sepsis Diagnosis and Treatmentlevel 3 · 0.05

Sources

Several sources describing one work is the point — it means the record rests on more than one authority.

openalexseen September 9, 2026
2025 · International Journal of Medical Informatics · 0 citations
https://openalex.org/W4415341811

Hybridized artificial intelligence system for reducing neonatal mortality in Nigeria · Sankore