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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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Mitigating algorithmic bias in AI-powered toxicology: Frameworks for explainable and equitable predictions in human health and environmental safety

2026Toxicology LettersJournalOpen access

10.1016/j.toxlet.2026.111924 Full text1 citations

Authors

6 authors across 5 institutions in 4 countries.

Olawale AjisafeFirst author
as printed: Olawale M. Ajisafe
Lydia Adeola Ogebule
Eghosasere Egbon
Olabanke Florence Olawuyi
- University of Calabar (NG)
Omobolaji Rosemary Olasilola
David B. OlawadeSenior authorCorresponding

Fields

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

Explainable Artificial Intelligence (XAI)level 3 · 0.57
Artificial Intelligence in Healthcare and Educationlevel 3 · 0.15
Adversarial Robustness in Machine Learninglevel 3 · 0.07

Sources

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

openalexseen September 9, 2026
2026 · Toxicology Letters · 1 citations
https://openalex.org/W7161837479

Mitigating algorithmic bias in AI-powered toxicology: Frameworks for explainable and equitable predictions in human health and environmental safety · Sankore