LASSO regression, RS calculation
REGRESSION
The radiomics features were normalized using Z-scoring and then downscaled using LASSO regression, and the optimal lnλ = -2.704 was determined by cross-validation, as shown in Fig. 
LASSO regression cross-validation diagram and regression coefficient diagram, the upper horizontal axis is the number of radiomics features corresponding to the models. The two vertical dashed lines in Fig. 4A show the two log (λ) values for minimum mean-squared error minimum and the increase of 1 SD (one standard deviation) mean-squared error minimum determined by cross-validation. Figure 4B shows that with the increase of log (λ), the radiomics features coefficients were gradually compressed to 0, and the number of features was reduced to 4 by the log (λ) with minimum mean-squared error minimum. LASSO, least absolute shrinkage and selection operator
Comparison of RS_LNM between two groups
ROC curve analysis of RS_LNM