AI RESEARCH
Fine-Tune, Don't Prompt, Your Language Model to Identify Biased Language in Clinical Notes
arXiv CS.CL
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ArXi:2603.10004v1 Announce Type: new Clinical documentation can contain emotionally charged language with stigmatizing or privileging valences. We present a framework for detecting and classifying such language as stigmatizing, privileging, or neutral. We constructed a curated lexicon of biased terms scored for emotional valence. We then used lexicon-based matching to extract text chunks from OB-GYN delivery notes (Mount Sinai Hospital, NY) and MIMIC-IV discharge summaries across multiple specialties.