Predicting distant metastasis in nasopharyngeal carcinoma using gradient boosting tree model based on detailed magnetic resonance imaging reports

Figure 1 Relative importance of top-ten variables based on the predictive full model. The full model included 23 variables. Only the top-ten variables with greater relative importance score are showed.

Figure 2 Performance comparison of the gradient boosting tree models and the tumor node-staging system. A: Performance assessment of the full model and reduced model. The full model included 23 selected variables. The reduced model only included the top-five variables. Area under the curve (AUC) is showed with 95% confidence interval (CI); B: Comparison of metastasis predictive performance among different predictive strategies in the whole dataset. Predictive strategies included using T-staging scores, N-stating scores, TN-staging scores, reduced model, and full model. The reduced model only included the top-five variables, while the full model included 23 selected variables. AUC is showed with 95%CI. AUC: Area under the curve.