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

arXiv:2512.19735 · cs.LG · Submitted 2025-12-17 · Read on arXiv

cs.LG

Submitted: 2025-12-17

Updated: 2026-09-30

Code: https://github.com/zgx-718/LLMs_bias_eva

Terminology

• AUROC — 1× in this paper · explained in 2 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Training-Free Framework — 1× in this paper · explained in 2 episodes

Sources

• Monitoring fairness in machine learning models that predict patient mortality in the ICU
• FairMedQA: Benchmarking Bias in Large Language Models for Medical Question Answering
• Aligning (Medical) LLMs for (Counterfactual) Fairness
• Metric-Fair Prompting: Treating Similar Samples Similarly
• Self-Debias: Self-correcting for Debiasing Large Language Models
• C2PO: Diagnosing and Disentangling Bias Shortcuts in LLMs
• Dual-Teacher De-biasing Distillation Framework for Multi-domain Fake News Detection
• Thinking Fair and Slow: On the Efficacy of Structured Prompts for Debiasing Language Models

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