Table 3.
3-fold cross-validation, (a), and hold-out test set performance, (b), of classifiers trained with radiomic, deep and hybrid datasets.
| (a) | |||||
|---|---|---|---|---|---|
| Training data | 3-fold cross-validation performance (95% CI) | ||||
| F2 | CohensKappa | AUC | Sensitivity | Specificity | |
| Rad |
0.8830 (0.8129, 0.9570) |
0.7350 (0.5300, 0.8562) |
0.8679 (0.7654, 0.9281) |
0.8920 (0.8164, 0.9762) |
0.8439 (0.6697, 0.9163) |
| Deep |
0.9577 (0.8267, 0.9675) |
0.8609 (0.6684, 0.9235) |
0.9311 (0.8338, 0.9615) |
0.9753 (0.8135, 0.9762) |
0.8870 (0.7701, 0.9639) |
| Hybrid |
0.9392 (0.8236, 0.9892) |
0.9164 (0.7175, 0.9444) |
0.9583 (0.8585, 0.9722) |
0.9306 (0.8056, 1) |
0.9861 (0.8282, 0.9868) |
| (b) | |||||
|---|---|---|---|---|---|
| Training data | Hold-out test-set performance | ||||
| F2 | CohensKappa | AUC | Sensitivity | Specificity | |
| Rad | 0.7767 | 0.5055 | 0.8192 | 0.8421 | 0.7179 |
| Deep | 0.3333 | 0.2648 | 0.8131 | 0.2941 | 0.9355 |
| Hybrid | 0.5063 | 0.4062 | 0.8710 | 0.4706 | 0.9032 |