Countries
Institutions
Fields
Rankings
Compare

Search institutions, scholars, countries and publications

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.

Built from

OpenAlex — works, authorships, subject classification
ROR — institutional identity
ORCID — researcher identity
Crossref — publisher confirmation

Browse

Countries
Institutions
Fields
Rankings
What we cover

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.

Predictive model for early detection of type 2 diabetes using patients' clinical symptoms, demographic features, and knowledge of diabetes

2024Health Science ReportsJournalOpen access

10.1002/hsr2.1834 Full text19 citations

Authors

8 authors across 5 institutions in 3 countries.

Taiwo Adetola OjurongbeFirst author
- Osun State University (NG)
Habeeb Abiodun Afolabi
- Osun State University (NG)
Adesola Oyekale
- Ladoke Akintola University of Technology (NG)
Kehinde Adekunle Bashiru
- Osun State University (NG)
Olubunmi Ayelagbe
- Ladoke Akintola University of Technology (NG)
Olusola Ojurongbe
- Ladoke Akintola University of Technology (NG)
Saddam Akber Abbasi
Nurudeen A AdegokeSenior authorCorresponding
as printed: Nurudeen A. Adegoke

Fields

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

Diabetes, Cardiovascular Risks, and Lipoproteinslevel 3 · 0.22
Artificial Intelligence in Healthcarelevel 3 · 0.12
Cancer Research and Treatmentlevel 3 · 0.08

Sources

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

openalexseen September 9, 2026
2024 · Health Science Reports · 19 citations
https://openalex.org/W4391223235

Predictive model for early detection of type 2 diabetes using patients' clinical symptoms, demographic features, and knowledge of diabetes · Sankore