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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.

Differentiating malignant and benign eyelid lesions using deep learning

2023Scientific ReportsJournalOpen access

10.1038/s41598-023-30699-5 Full text20 citations

Authors

11 authors across 11 institutions in 2 countries.

Min Joung LeeFirst authorCorresponding
- Sacred Heart Hospital (NG)
Min Kyu Yang
Sang In Khwarg
Eun Kyu Oh
Youn Joo Choi
Namju Kim
Hokyung Choung
Chang Won Seo
Yun Jong Ha
Min Ho ChoCorresponding
Bum-Joo ChoSenior authorCorresponding
- Sacred Heart Hospital (NG)

Fields

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

Nonmelanoma Skin Cancer Studieslevel 3 · 1.00
Cutaneous Melanoma Detection and Managementlevel 3 · 1.00
Salivary Gland Tumors Diagnosis and Treatmentlevel 3 · 0.99

Sources

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

openalexseen September 9, 2026
2023 · Scientific Reports · 20 citations
https://openalex.org/W4324128889

Differentiating malignant and benign eyelid lesions using deep learning · Sankore