Model | Train | Validation | ||||
---|---|---|---|---|---|---|
AUC (%) | Sensitivity (%) | Specificity (%) | AUC (%) | Sensitivity (%) | Specificity (%) | |
Conventional statistics (rule-based) | 93.7 (90.1–96.6, 95% CI) | 89.7 (82.5–95.6, 95% CI) | 97.7 (96.9–98.6, 95% CI) | 91.1 (80.6–98.9, 95% CI) | 84.6 | 97.7 (97.3–98.1, 95% C.I |
Decision tree | 97.0 (95.0–98.6, 95% CI) | 95.4 (90.7–99.7, 95% CI) | 89.1 (87.2–90.8, 95% CI) | 98.0 (96.7–99.0, 95% CI) | 100 | 87.0 (86.1–87.8, 95% CI) |
Logistic regression | 99.3 (98.8–99.7, 95% CI) | 95.4 (90.5–98.9, 95% CI) | 96.8 (95.6–97.7, 95% CI) | 98.8 (98.3–99.2, 95% CI) | 100 | 89.7 (88.8–90.5, 95% CI) |
Random forest | 99.3 (98.6–99.7, 95% CI) | 95.4 (90.3–98.9, 95% CI) | 96.9 (95.9–97.8, 95% CI) | 99.4 (98.8–99.8, 95% CI) | 100 | 95.7 (95.1–96.2, 95% CI) |
XGBoost | 99.3 (98.8–99.8, 95% CI) | 95.4 (90.6–99.0, 95% CI) | 96.8 (95.7–97.7, 95% CI) | 99.4 (98.5–99.9, 95% CI) | 100 | 93.7 (93.1–94.3, 95% CI) |