Fig. 2

Ten-fold cross-validation results using the LASSO method. (a) The binomial deviance metrics (the y-axis) were plotted against log(λ) (the bottom x-axis). The top x-axis indicates the number of predictors with the given log(λ). Red dots indicate the average AUC for each model at the given λ, and vertical bars through the red dots show the upper and lower values of the binomial deviance in the cross-validation process. The vertical black lines define the optimal λ, where the model provides its best fit to the data. As a result, the optimal λ of 0.1047237, with log(λ) = − 2.256430, was selected. (b) The LASSO coefficient profiles of the 45 radiomic features are depicted. The vertical line was plotted at the given λ. For the optimal λ, eight features with non-zero coefficients were selected