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Calibrated Transfer Learning for Survival Prediction and Treatment Inference
Historical survival data can improve prediction in a cohort with few events, but prognostic differences can make borrowing harmful. To borrow while adapting, we propose calibrated transfer learning for the Cox model, in which a historical risk function enters the target analysis as a fixed offset wi
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