Fig. 4From: Dynamic contrast-enhanced MRI radiomics nomogram for predicting axillary lymph node metastasis in breast cancerRadiomics feature selection using the LASSO regression algorithm in the primary cohort. A. Selection of the parameter (λ) in the LASSO model via 10-fold cross-validation depending on the minimum criteria. The binomial deviance curve versus log (lambda) was plotted, and the left vertical line corresponds to the optimal value of the minimum criterion; the right vertical line corresponds to the optimal value of the 1-SE criteria. The optimal λ value of 0.0127with threshold log (λ) of was − 4.32 was selected. B. LASSO coefficient profiles of the 55 features. Vertical line was plotted at the value selected using 10-fold cross-validation, where optimal λ resulted in 14 nonzero coefficients. C. The receiver operating characteristic curves (ROC) of the radiomics signature in the training and validation cohortsBack to article page