Fig. 2From: A radiomics signature derived from CT imaging to predict MSI status and immunotherapy outcomes in gastric cancer: a multi-cohort studyRadiomics feature selection by using the least absolute shrinkage and selection operator (LASSO) logistic regression. (a) The selection of tuning parameter (λ) in the LASSO model used 10-fold cross-validation via minimum criteria. The AUC curve was plotted versus log (λ). (b) LASSO coefficient profiles of the radiomics features. A vertical line was plotted at the optimal λ value, which resulted in 9 features with nonzero coefficientsBack to article page