Medicine and Health

Efficient Detection of Stigmatizing Language in Electronic Health Records via In-Context Learning: A Comparative Analysis and Validation Study

H. Chen, M. Alfred, et al.

This groundbreaking study by Hongbo Chen, Myrtede Alfred, and Eldan Cohen delves into the effectiveness of in-context learning (ICL) for identifying stigmatizing language in Electronic Health Records. Remarkably, ICL surpassed traditional methods with superior performance despite utilizing less data, highlighting its potential in bias reduction within healthcare documentation.

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