Transfer learning with deployment-covariate recalibration for survival prediction under covariate shift

TL;DR - Pan et al. introduce CoxRTL, a transfer-learning method for survival prediction that recalibrates external cohort data under covariate shift. It targets settings with limited training data and no observed deployment outcomes.

• Uses external cohorts to improve target-cohort survival prediction.
• Recalibrates for differences between training and deployment covariates.
• Designed to work without deployment outcome labels.
• Addresses data scarcity in time-to-event modeling.