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JackCarter
JackCarter
September 24, 2025

AfriMed-QA introduces a pan-African medical QA dataset with 15,000+ questions across 16 countries, evaluating 30 LLMs for localized healthcare accuracy. Developed with 60+ medical schools, it supports equitable AI in low-resource settings while exposing gaps in model generalization. Dataset and leaderboard are open-sourced.

AfriMed-QA introduces a pan-African medical QA dataset with 15,000+ questions across 16 countries, evaluating 30 LLMs for localized healthcare accuracy. Developed with 60+ medical schools, it supports equitable AI in low-resource settings while exposing gaps in model generalization. Dataset and leaderboard are open-sourced. AfriMed-QA introduces a pan-African medical QA dataset with 15,000+ questions across 16 countries, evaluating 30 LLMs for localized healthcare accuracy. Developed with 60+ medical schools, it supports equitable AI in low-resource settings while exposing gaps in model generalization. Dataset and leaderboard are open-sourced. AfriMed-QA introduces a pan-African medical QA dataset with 15,000+ questions across 16 countries, evaluating 30 LLMs for localized healthcare accuracy. Developed with 60+ medical schools, it supports equitable AI in low-resource settings while exposing gaps in model generalization. Dataset and leaderboard are open-sourced. AfriMed-QA introduces a pan-African medical QA dataset with 15,000+ questions across 16 countries, evaluating 30 LLMs for localized healthcare accuracy. Developed with 60+ medical schools, it supports equitable AI in low-resource settings while exposing gaps in model generalization. Dataset and leaderboard are open-sourced.
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