Feature importance & performance of models for the efficacy of NVBG
There were statistically significant differences in JIC and exposure to risk factors postoperatively (Table 
Univariate and multivariate analysis for efficacy of NVBG in the training cohort
Radiomics features selected by LASSO to determine the efficacy of NVBG (In the training cohort, the C-R model had an AUC of 0.818 (95% CI: 0.743–0.893), predicting sensitivity of 0.778 and specificity of 0.729 at the optimum cut-off of 0.308. In the validation cohort, the AUC of C-R model was 0.747 (95% CI: 0.564–0.930), with a predicting sensitivity of 0.556 and specificity of 0.860 at the optimum cut-off of 0.480 (Fig. 
Performance of three models for predicting efficacy of NVBG
ROC curves (A nomogram was developed to visualize the C-R model (Fig. 
Nomograms of the C-R model for predicting the efficacy of NVBG (