Counterfactual Auditing of Bias in Open-Source Large Language Models for Clinical Triage

Excerpt

arXiv:2610.01963v1 Announce Type: cross Abstract: Emergency department (ED) triage is a high-stakes prioritization task in which demographic, socioeconomic, and system-context information may improperly influence acuity assignment. Although open-source large language models (LLMs) are increasingly considered for local and privacy-preserving clinical decision support, it remains unclear how counterfactual bias varies across model families, sizes, medical-domain models, and domain-adapted models.