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stat.ME2026
Towards Fair Predictions: Group Conditional Concordance Index to Quantify Fairness in Time-to-Event Prognostication
Haoyuan Wang, Riddhiman Bhattacharya, Richardo Henao +3
Fairness metrics are essential for rigorously defining, quantifying, and mitigating biases in predictive models. While most existing metrics focus on binary classification tasks, f…
stat.AP2026
Distributionally Robust Transfer Learning with Structurally Missing Covariates, with Application to Cross-National Cardiac Arrest Prediction
Siqi Li, Chuan Hong, Ziye Tian +9
Deploying clinical prediction models across healthcare systems often fails when key training covariates are unavailable at deployment and labeled outcomes are limited in the target…