Table 3.
Detailed performance metrics for the four models in training set
| Models | AUROC | Sensitivity | Specificity | PPV | NPV |
|---|---|---|---|---|---|
| (95%CI) | (95%CI) | (95%CI) | (95%CI) | (95%CI) | |
| Mutil-tree XGBoost | 0.985 | 0.934 | 0.938 | 0.943 | 0.929 |
| (0.982–0.987) | (0.924–0.944) | (0.928–0.949) | (0.933–0.952) | (0.918–0.940) | |
| Simple-tree XGBoost | 0.971 | 0.915 | 0.900 | 0.908 | 0.907 |
| (0.967–0.975) | (0.903–0.926) | (0.887–0.913) | (0.897–0.920) | (0.894–0.919) | |
| Logistic-11 | 0.869 | 0.712 | 0.878 | 0.864 | 0.738 |
| (0.858–0.879) | (0.694–0.731) | (0.864–0.892) | (0.848–0.880) | (0.720–0.755) | |
| Logistic-6 | 0.864 | 0.727 | 0.860 | 0.849 | 0.744 |
| (0.853–0.875) | (0.709–0.746) | (0.845–0.875) | (0.834–0.865) | (0.726–0.761) |
AUC: area under the receiver operating characteristic curve; PPV: positive predictive value; NPV: negative predictive value; CI: Confidence Interval