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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.

Machine learning models for plant fungal disease detection and risk prediction: A systematic review

2026Industrial Crops and ProductsJournalOpen access

10.1016/j.indcrop.2026.123877 Full text1 citations

Authors

7 authors across 8 institutions in 4 countries.

Mohammad MehdizadehFirst authorCorresponding
Anahita Omidi
Egbune A. Chukwuekwu
Onyewuchi H. Njoku
- Lead City University (NG)
- University of Ibadan (NG)
Olumide T. Adeleke
- Bowen University (NG)
Emodi C. Rita
- Nnamdi Azikiwe University (NG)
Awelani MutshembeleSenior author
- South African Medical Research Council (ZA)

Fields

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

Smart Agriculture and AIlevel 3 · 0.14
AI in cancer detectionlevel 3 · 0.06
Artificial Intelligence in Healthcarelevel 3 · 0.04

Sources

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

openalexseen September 9, 2026
2026 · Industrial Crops and Products · 1 citations
https://openalex.org/W7167802890

Machine learning models for plant fungal disease detection and risk prediction: A systematic review · Sankore