Figure 3.

Radiomics feature selection performed using LASSO logistic regression for establishing the rad score. (A–C) and (D–E) describe the results of radiomics analysis for 4CV and 2CV images, respectively. In 4CV analysis, seven features are selected by identifying the best λ with λ.1-SE in the LASSO model (A,B), and their weights are listed in (C). In 2CV analysis, no features can be selected with the optimal λ values (D,E). LASSO, least absolute shrinkage and selection operator; 4CV, four-chamber view; 2CV, two-chamber view; λ, penalty regularization parameter; λ.min, minimum criteria; λ.1-SE, 1-standard error of the minimum criteria.