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Clinical and Translational Medicine
Fig. 2 | Clinical and Translational Medicine

Fig. 2

From: Personalized CT-based radiomics nomogram preoperative predicting Ki-67 expression in gastrointestinal stromal tumors: a multicenter development and validation cohort

Fig. 2

Texture feature selection using the least absolute shrinkage and selection operator (LASSO) binary logistic regression model. a LASSO coefficient profiles, displaying thirty texture features. A coefficient profile plot was produced against the log (lambda) sequence. Each colored line represents the coefficient of individual feature. b Tuning parameter (log lambda) selection in the LASSO model used tenfold cross-validation via minimum criteria. Vertical dotted lines were drawn at the selected λ values

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