Table 2 Performances of machine learning models for prediction of tumor recurrence in the training and test set
Models | Training set | Test set | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
AUC (95% CI) | Accuracy (%) | Sensitivity (%) | Specificity (%) | P value | AUC (95% CI) | Accuracy (%) | Sensitivity (%) | Specificity (%) | P value | |
Clinicopathological model | 0.67 (0.59–0.74) | 66.9 | 48.2 | 85.3 | Reference | 0.61 (0.44–0.78) | 81.3 | 33.3 | 89.1 | Reference |
Clinicopathological + radiomics model | 0.78 (0.70–0.85) | 75.0 | 76.8 | 31.0 | 0.042 | 0.77 (0.60–0.94) | 70.3 | 66.7 | 70.9 | 0.192 |