FIGURE 3.

Radiomic feature selection from signature heatmap using the least absolute shrinkage and selection operator (LASSO) logistic regression model. (A) The heat map of relationship among texture analysis parameters. (B) Identification of the optimal penalization coefficient lambda (λ) in the LASSO model used 10‐fold cross‐validation and the minimum criterion. (C) Lasso coefficient profiles of the 56 radiomic features. The dotted vertical line was plotted at the value selected using 10‐fold cross‐validation in (A), for which the optimal λ resulted in 10 non‐zero coefficients