Table 3.
Receiver-operating characteristic curves for performance of LR, the ANN, and the radiologists on the test set
| ROC analysis | LR | ANN | Radiologist 1 | Radiologist 2 | Radiologist 3 | Radiologist 4 | Radiologist 5 |
|---|---|---|---|---|---|---|---|
| AUC value | 0.87 (0.77, 0.94) | 0.87 (0.77, 0.94) | 0.88 (0.79, 0.95) | 0.79 (0.68, 0.88) | 0.85 (0.75, 0.93) | 0.91 (0.82, 0.97) | 0.85 (0.75, 0.93) |
| Cutoff value yielding the highest accuracy | 0.19 | 0.26 | 3 | 3 | 4 | 3 | 3 |
| Sensitivity % | 93.1 (77.2, 99.0) | 93.1 (77.2, 99.0) | 96.6 (82.2, 99.4) | 93.1 (77.2, 99) | 51.7 (32.5, 70.5) | 100 (87.9, 100) | 89.7 (72.6, 97.7) |
| Specificity % | 70.7 (54.5, 83.9) | 70.7 (54.5, 83.9) | 73.2 (57.1, 85.8) | 51.2 (35.1, 67.1) | 100 (91.3, 100) | 75.6 (59.7, 87.6) | 75.6 (59.7, 87.6) |
| Accuracy | 0.80 (54.5, 83.9) | 0.80 (54.5, 83.9) | 0.83 (71.9, 90.8) | 0.70 (57.8, 80.3) | 0.80 (54.5, 83.9) | 0.86 (75.2, 82.9) | 0.80 (54.5, 83.9) |
Numbers in parentheses are 95% CI
ANN artificial neural network, AUC area under the receiver-operating characteristic curve, LR logistic regression, ROC receiver-operating characteristic curve