Table 5. Performances of the HLG-ML model, radiologists, and YEARS algorithm in diagnosing APE in the validation group.
| Methods | AUC (95% CI) | Sensitivity (95% CI), % | Specificity (95% CI), % | Youden index |
|---|---|---|---|---|
| HLG-ML | 0.810 (0.669, 0.952) | 87.1 (70.2, 96.4) | 75.0 (42.8, 94.5) | 0.621 |
| Reader 1 | 0.508 (0.335, 0.681) | 51.6 (33.1, 69.8) | 50.0 (21.1, 78.9) | 0.016 |
| Reader 2 | 0.504 (0.354, 0.654) | 25.8 (11.9, 44.6) | 75.0 (42.8, 94.5) | 0.008 |
| Reader 3 | 0.527 (0.363, 0.691) | 38.7 (21.8, 57.8) | 66.7 (34.9, 90.1) | 0.050 |
| YEARS algorithm | 0.618 (0.469, 0.767) | 90.3 (74.2, 98.0) | 33.3 (9.9, 65.1) | 0.237 |
HLG-ML, holistic lung graph-based machine learning; APE, acute pulmonary thromboembolism; AUC, area under the curve; CI, confidence interval.