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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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Coverage is partial and says so. A country appears with its research output only once its works have been swept; until then the portal shows whatever the graph happens to hold for it and labels it as exactly that.

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

2026BMC Medical Informatics and Decision MakingJournalOpen access

10.1186/s12911-026-03796-4 Full text0 citations

Authors

6 authors across 4 institutions in 2 countries.

Mary Ofuru KamaFirst authorCorresponding
- Ebonyi State University (NG)
- Veritas University (NG)
- University of Nigeria (NG)
Ifeyinwa Angela Ajah
- Ebonyi State University (NG)
Anayo Chukwu IkegwuCorresponding
- Veritas University (NG)
Adaora Angela Obayi
- University of Nigeria (NG)
Felix Oshiorenoya Uloko
- Veritas University (NG)
Immaculate Chidimma OgbuaguSenior author
- Veritas University (NG)

Fields

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

Hemoglobinopathies and Related Disorderslevel 3 · 0.91
Artificial Intelligence in Healthcare and Educationlevel 3 · 0.01
Climate Change and Health Impactslevel 3 · 0.01

Sources

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

openalexseen September 9, 2026
2026 · BMC Medical Informatics and Decision Making · 0 citations
https://openalex.org/W7207879871

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