Figure 3.

Selection of radiomics features using the least absolute shrinkage and selection operator (LASSO) binary logistic regression. Turning parameter (λ) selection in the LASSO model used a 10-fold cross-validation via minimum criteria, and optimal λ resulted in 30 nonzero coefficients. The area under the receiver operating characteristic (AUC) curve was plotted versus log (λ). Dotted vertical lines were drawn at the optimal values by using the minimum criteria and 1 standard error of the minimum criteria (the 1-SE criteria) according to 10-fold cross-validation. The minimum criteria were chosen as the optimal λ with the largest AUC in the training data set, which resulted in 30 non-zero coefficients.