Figure 5.

The least absolute shrinkage and selection operator (LASSO) binary logistic regression model used to select radiomics features. (A) Tuning parameter (λ) selection in the LASSO model used 10-fold cross-validation via minimum criteria. The area under the receiver operating characteristic curve (AUC) is plotted versus log(λ). Dotted vertical lines are drawn at the optimal values by using the minimum criteria and the 1 standard error of the minimum criteria (the 1-SE criteria). (B) LASSO coefficient profiles of the 386 radiomics features. A coefficient profile plot was produced against the log(λ) sequence. As a result, 11 non-zero coefficients were chosen.