Table 3.
Binary classification of rupture risk involving small UIAs in the test dataset using various CNN architectures. CI, confidence interval.
| Type | Models | Sensitivity (95% CI) | Specificity (95% CI) | Overall Accuracy (95% CI) | F1 Score (95% CI) |
|---|---|---|---|---|---|
| Multi-view | ResNet50 | 81.82 (66.76–91.2)% | 81.63 (67.50–90.76)% | 81.72 (66.98–90.92)% | 80.90 (67.29–91.81)% |
| Multi-view | AlexNet | 63.64 (47.74–77.17)% | 87.76 (74.54–94.92)% | 76.34 (62.31–88.19)% | 71.79 (55.13–85.00)% |
| Multi-view | VGG16 | 68.18 (52.29–80.93)% | 79.59 (65.24–89.28)% | 74.19 (58.93–85.60)% | 71.43 (55.42–84.28)% |
| Multi-view | ResNet101 | 68.18 (52.29–80.93)% | 77.55 (63.01–87.75)% | 73.12 (57.71–84.66)% | 70.59 (55.42–84.28)% |
| Multi-view | ResNet152 | 54.55 (39.00–69.31)% | 87.76 (74.54–94.92)% | 72.04 (58.18–85.68)% | 64.86 (47.46–79.79)% |
| Single-view | ResNet50 | 50.00 (34.79–65.21)% | 77.55 (63.01–87.75)% | 64.52 (48.93–78.45)% | 57.14 (40.82–73.69)% |