Table 2.
Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristic curve (AUC) along with the 95% confidence interval (CI) for AUC for each classifier.
| Classifier | DCE | T2w | Image fusion | Feature fusion | Classifier fusion |
|---|---|---|---|---|---|
| AUC [95% CI] | 0.85 [0.82, 0.88] | 0.78 [0.75, 0.81] | 0.85 [0.82, 0.88] | 0.87 [0.84, 0.89] | 0.86 [0.83, 0.88] |
| Sensitivity (%) | 75.9 | 69.8 | 76.5 | 77.9 | 77.6 |
| Specificity (%) | 76.5 | 72.7 | 77.1 | 78.5 | 77.1 |
| PPV (%) | 89.7 | 87.3 | 90.0 | 90.7 | 90.1 |
| NPV (%) | 54.2 | 47.3 | 55.0 | 56.9 | 56.2 |
Sensitivity and specificity presented are for the optimal operating point determined using a metric for cut-off value that minimizes m = (1 − sensitivity)2 + (1 − specificity)2.