Figure 3.

Radiomics feature selection using the least absolute shrinkage and selection operator (LASSO) regression model in the training cohort. The selection of the optimal penalization coefficient lambda (λ) in the LASSO model used the fivefold cross‐validation (CV) process via minimum criteria. The area under the curve (AUC) was plotted versus log (λ). Dotted vertical lines were drawn at the optimal values using the minimum criteria and the 1 standard error of the minimum criteria (the 1−SE criteria). A λ value of 0.0853 with log (λ) −2.46 was chosen, where optimal λ resulted in five nonzero coefficients. [Color figure can be viewed at wileyonlinelibrary.com]