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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.

Performance and clinical utility of image-based machine learning models for the diagnosis of neglected tropical diseases in low- and middle-income countries: a systematic review

2026BMC Infectious DiseasesJournalOpen access

10.1186/s12879-026-13784-8 Full text0 citations

Authors

6 authors across 4 institutions in 2 countries.

David Chinaecherem InnocentFirst authorCorresponding
- University of Port Harcourt (NG)
Precious Ebube Anyakorah
- Center for Clinical Care and Research in Nigeria (NG)
Rejoicing Chijindum Innocent
- Center for Clinical Care and Research in Nigeria (NG)
Ikechukwu Nosike Simplicius Dozie
- Federal University of Technology Owerri (NG)
Uchechukwu M. Chukwuocha
- Federal University of Technology Owerri (NG)
as printed: Uchechukwu Madukaku Chukwuocha
Chiagoziem Ogazirilem EmeroleSenior author
- Federal University of Technology Owerri (NG)

Fields

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

Digital Imaging for Blood Diseaseslevel 3 · 0.56
Parasitic Diseases Research and Treatmentlevel 3 · 0.10
COVID-19 diagnosis using AIlevel 3 · 0.06

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 Infectious Diseases · 0 citations
https://openalex.org/W7164821635

Performance and clinical utility of image-based machine learning models for the diagnosis of neglected tropical diseases in low- and middle-income countries: a systematic review · Sankore