Table 9.
ROC curve parameters of models in the validation set
| Marker | AUC | 95% CI | Specificity | Sensitivity | Youden index | Accuracy | Precision | F1 Score |
|---|---|---|---|---|---|---|---|---|
| XGBoost | 0.855 | 0.788-0.922 | 79.87% | 76.67% | 56.54% | 79.35% | 76.67% | 54.76% |
| AdaBoost | 0.857 | 0.791-0.924 | 90.91% | 63.33% | 54.24% | 86.41% | 63.33% | 60.32% |
| Random Forest | 0.751 | 0.659-0.843 | 93.51% | 56.67% | 50.17% | 87.50% | 56.67% | 59.65% |
| SVM | 0.751 | 0.659-0.843 | 93.51% | 56.67% | 50.17% | 87.50% | 56.67% | 59.65% |
| LASSO | 0.859 | 0.789-0.930 | 83.12% | 73.33% | 56.45% | 81.52% | 73.33% | 56.41% |
Note: ROC, receiver operating characteristic; XGBoost, eXtreme Gradient Boosting; AdaBoost, Adaptive Boosting; SVM, Support Vector Machine; LASSO, Least Absolute Shrinkage and Selection Operator.