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Fig. 4 | Radiation Oncology

Fig. 4

From: Radiomics for prediction of radiation-induced lung injury and oncologic outcome after robotic stereotactic body radiotherapy of lung cancer: results from two independent institutions

Fig. 4

a Regularization and feature selection by repeated cross validation (CV) in a combined Coxnet model for development of lung fibrosis (LF) in the training set. The optimal model arose at an alpha-value of 0.5 × 10–2 where a mean concordance index (CCI) of 0.67 ± 0.12 was achieved. b Coefficients for the optimal Coxnet model that comprised 4 clinical/dosimetric and 7 radiomics features. c Kaplan–Meier curves displaying performance of the radiomics model in the training and test cohorts when stratifying patients into low and high risk groups by the respective medians of the model risk scores (train: 40.2, range 31.4–46.0; test: 42.4, range 25.0–60.4); pCox: Significance level for the model risk score used as a continuous variable in a univariate Cox regression analysis

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