Skip to main content
Fig. 4 | Cancer Imaging

Fig. 4

From: Application of contrast-enhanced CT radiomics in prediction of early recurrence of locally advanced oesophageal squamous cell carcinoma after trimodal therapy

Fig. 4

Feature selection using the least absolute shrinkage and selection operator (LASSO) regression. a Turning optimal parameter lambda (λ) using 10-fold cross-validation and minimum criterion in Lasso model. The left and right dashed lines represent the minimum criterion and the 1-standard error (1-SE) criterion, respectively. The 1-SE criterion has been applied. b Lasso coefficient profiles of the 263 radiomics features. The picture shows the optimal λ value of 0.025. 11 features with non-zero coefficients have been selected

Back to article page

Cancer Imaging

ISSN: 1470-7330

Contact us