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Advancing data science research education in Africa through datathon-driven innovations

Abstract The rapid expansion of biomedical datasets generated by international research programs across Africa highlights an urgent need for advanced data science expertise to translate these resources into impactful interventions. We designed an innovative training model for a data science research...

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Tallennettuna:
Päätekijät: Seydou Doumbia, Fousseyni Kane, Oudou Diabate, Cheickna Cisse, Ibrahim Sanogo, Mamadou D. Coulibaly, Fatoumata G. Fofana, Alexandre Delamou, Abdoul Habib Beavogui, Sidibé M’Baye Thiam, Jian Li, Moussa Keïta, Nafomon Sogoba, Cheick Oumar Tangara, Samuel Kakraba, Mamadou Wele, Mahamadou Diakite, Mahamoudou Toure, Jeffrey G. Shaffer
Aineistotyyppi: Artigo
Kieli:Inglês
Julkaistu: Nature Portfolio 2026-03-01
Sarja:Scientific Reports
Aiheet:
Artificial intelligence
Africa
Datathon
Data science
Malaria
Machine learning
Linkit:https://doi.org/10.1038/s41598-026-41474-7
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