Fig. 3

Radiomics feature selection using the least absolute shrinkage and selection operator (LASSO) binary logistic regression model. a Optimal parameter (lambda) selection in the LASSO model used 10-fold cross-validation via minimum criteria. The partial likelihood deviance (binomial deviance) curve was plotted versus log (lambda). Dotted vertical lines were drawn at the optimal values using the minimum criteria and the 1 SE of the minimum criteria (the 1-SE criteria). b LASSO coefficient profiles of the 2041 features. A coefficient profile plot was produced against the log (lambda) sequence. A vertical line was drawn at the value selected, using 10-fold cross-validation, where optimal lambda resulted in 15 features with nonzero coefficients. c ROC curves of radiomics signatures in primary cohorts. d Validation cohort