SurvSHAP(t) Code for Radiomics-Augmented Survival Modeling in NSCLC

This repository provides representative Python code illustrating the LASSO-Cox survival modeling and time-dependent AUC (TD-AUC) evaluation workflow used in the accompanying manuscript on radiomics-augmented survival analysis. The code uses simulated (toy) data only and does not include any patient-level clinical or imaging data. Full clinical preprocessing pipelines and raw patient data are not publicly released due to ethical approval constraints and patient privacy considerations. The purpose of this repository is to ensure methodological transparency rather than exact numerical reproducibility.