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Evaluating and addressing demographic disparities in medical large language models: a systematic review
45
Zitationen
11
Autoren
2025
Jahr
Abstract
Biases are observed in large language models across various medical domains. While bias detection is improving, effective mitigation strategies are still developing. As LLMs increasingly influence critical decisions, addressing these biases and their resultant disparities is essential for ensuring fair artificial intelligence systems. Future research should focus on a wider range of demographic factors, intersectional analyses, and non-Western cultural contexts.
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