An evaluation of GPT-4, Claude-3, and LLaMA-3 on six healthcare tasks finds low accuracy and demographic unfairness, with less favorable predictions for African American patients.
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Unveiling Performance Challenges of Large Language Models in Low-Resource Healthcare: A Demographic Fairness Perspective
An evaluation of GPT-4, Claude-3, and LLaMA-3 on six healthcare tasks finds low accuracy and demographic unfairness, with less favorable predictions for African American patients.