Figure 2.

Selection of radiomics features via the least absolute shrinkage and selection operator (LASSO) regression algorithm. (a) Tuning parameter (λ) selection in LASSO model used tenfold cross-validation via 1-standard error criterion. The optimal values of the LASSO tuning parameter (λ) are indicated by the dotted vertical lines (the right one), and a value λ of 0.086 was chosen. (b) LASSO coefficient profiles of the 952 radiomics features. A coefficient profile plot was generated versus the selected log λ value using tenfold cross-validation. Twelve radiomics features with non-zero coefficients were finally selected.