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

ICL offers a robust and flexible solution for detecting stigmatizing language in EHRs, offering a more data-efficient and equitable alternative to conventional machine learning methods. These findings suggest that ICL could enhance bias detection in clinical documentation while reducing the reliance on extensive labeled datasets.