Figure 2.

The least absolute shrinkage and selection operator (LASSO) algorithm and 10-fold cross-validation were used to extract the optimal subset of radiomic features. (A) Tuning parameter (lambda, λ) selection in the LASSO model used 10-fold cross validation for the training set. The mean deviance (goodness-of-fit statistics, red dots) was plotted vs. log (λ), error bars displaying the range of standard error. Dotted vertical lines were drawn at the point of minimum deviance and at the point where maximum λ was obtained among errors smaller than the standard error of minimum deviance. (B) LASSO coefficient profiles of the 73 texture features.