Improving Fairness of Large Language Model-Based ICU Mortality Prediction via Case-Based Prompting

Excerpt

arXiv:2512.19735v4 Announce Type: replace Abstract: Accurately predicting mortality risk in intensive care unit (ICU) patients is critical for clinical decision-making. Large language models (LLMs) are increasingly explored for clinical prediction using structured medical data, but their outputs may exhibit demographic disparities. Mitigating such disparities without degrading predictive performance remains challenging. We systematically investigate demographic bias in LLM-based ICU mortality pr