Pretreatment Prediction of Relapse Risk in Patients with Osteosarcoma Using Radiomics Nomogram Based on CT: A Retrospective Multicenter Study

Figure 2

Texture feature selection using LASSO Cox regression model. (a) The partial likelihood deviation was plotted versus log (). The optimal parameter () was selected using a sixfold cross-validation and 1 standard error rule. The optimal of 0.179 with was selected. (b) LASSO coefficient profiles of 200 radiomics features were based on CT images. Finally, four features were selected, which are shown with black vertical dotted lines in the figure.

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