Radiomics feature selection and rad-score construction
REGRESSION
A total of 1746 radiomics features were extracted, of which 1251 (71.65%) had an intra-class correlation coefficient of 0.8 or more in the reproducibility analysis. These were chosen for subsequent analysis. After dimension reduction with MRMR, the 20 best features were selected. The Lasso algorithm was used for further dimension reduction (Radiomic feature selection using a least absolute shrinkage and selection operator (LASSO) binary logistic regression model 