Table 2 Model performance on test set data for predicting 30-day major adverse limb event or death following lower extremity open revascularization using pre-operative features.
From: Predicting outcomes following lower extremity open revascularization using machine learning
AUROC (95% CI) | Accuracy (95% CI) | Sensitivity | Specificity | PPV | NPV | |
|---|---|---|---|---|---|---|
XGBoost | 0.93 (0.92–0.94) | 0.86 (0.85–0.87) | 0.84 | 0.89 | 0.90 | 0.83 |
Random forest | 0.92 (0.91–0.93) | 0.85 (0.84–0.86) | 0.84 | 0.86 | 0.86 | 0.83 |
Naïve bayes | 0.87 (0.86–0.88) | 0.85 (0.84–0.86) | 0.83 | 0.85 | 0.86 | 0.82 |
RBF SVM | 0.85 (0.84–0.86) | 0.77 (0.75–0.79) | 0.75 | 0.80 | 0.83 | 0.71 |
MLP ANN | 0.80 (0.78–0.82) | 0.73 (0.70–0.75) | 0.71 | 0.75 | 0.79 | 0.69 |
Logistic regression | 0.63 (0.61–0.65) | 0.58 (0.56–0.60) | 0.55 | 0.71 | 0.60 | 0.56 |
