Fairness Audit and Debiasing of Machine Learning Models for Sepsis Mortality Prediction Across Demographic Subgroups: A Multi-Metric Study with Accuracy–Fairness Tradeoff Analysis
Three ML models were trained on a 10,000-patient cohort calibrated to published MIMIC-IV sepsis statistics, and a four-metric fairness audit was performed across race/ethnicity, sex, and insurance type.