Figure S1.

Radiomics feature selection using the least absolute shrinkage and selection operator (LASSO) regression model. (A) LASSO coefficient profiles of the radiomics features. As the tuning parameter (λ) increased using 5-fold cross-validation, more coefficients tended to approach 0 and the optimal non-zero coefficients generated, which yielded a set of the optimal radiomics features; (B) the partial likelihood deviance from the LASSO regression cross-validation procedure was plotted against log(λ).