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Insights into Imaging
Fig. 3 | Insights into Imaging

Fig. 3

From: Development of a simplified model and nomogram in preoperative diagnosis of pediatric chronic cholangitis with pancreaticobiliary maljunction using clinical variables and MRI radiomics

Fig. 3

Radiomics feature selection using the least absolute shrinkage and selection operator (LASSO) regression model. a Tuning parameter (λ) selection in LASSO model used tenfold cross-validation via minimum criterion. The optimal values of the LASSO tuning parameter (λ) are indicated by the dotted vertical lines, and a value λ of 0.064 with log(λ) = − 2.743 was selected. b LASSO coefficient profiles of the 1056 radiomics features. A coefficient profile plot was produced versus the log (λ) sequence. The dotted vertical line was drawn at the value selected using tenfold cross-validation, in which the selected λ resulted in eight nonzero coefficients. c The most predictive subset of feature was chosen and the corresponding coefficients were evaluated in the training cohort

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