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Large Language Models in Medical Diagnostics: Scoping Review With Bibliometric Analysis
Similarly, Yang et al [145] showed race-based tendencies in both GPT-3.5-turbo and GPT-4 models, including generating biased patient backgrounds, associating diseases with specific demographic groups, favoring White patients in treatment recommendations, and showing disparities in projected cost, hospitalization duration, and prognosis [145]. Such biased models could negatively impact the quality of diagnoses that patients receive.
J Med Internet Res 2025;27:e72062
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Clinical Management of Wasp Stings Using Large Language Models: Cross-Sectional Evaluation Study
J Med Internet Res 2025;27:e67489
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