Table 3. Performance Levels for Human and Machine Experiments Using Patient Partitioned Dataa.
Method/Data set | Human H |
DCNN-A WS |
DCNN-U WS |
DCNN-A NSG |
DCNN-U NSG |
DCNN-A NS |
DCNN-U NS |
---|---|---|---|---|---|---|---|
Accuracy | 90.2 | 88.7 (0.7) | 83.1 (0.9) | 88.8 (0.7) | 83.1 (0.5) | 88.4 (0.5) | 82.4 (0.5) |
Sensitivity | 86.4 | 84.6 (0.9) | 72.3 (2.2) | 85.3 (1.6) | 71.7 (1.4) | 84.5 (0.9) | 71.0 (1.3) |
Specificity | 93.2 | 92.0 (0.7) | 91.8 (0.6) | 91.6 (1.2) | 92.2 (0.5) | 91.5 (0.7) | 91.4 (0.3) |
PPV | 91.0 | 89.4 (1.1) | 87.5 (1.1) | 89.2 (1.1) | 88.0 (0.7) | 88.9 (1.0) | 86.9 (0.5) |
NPV | 89.6 | 88.2 (1.0) | 80.6 (1.4) | 88.6 (1.1) | 80.2 (1.1) | 88.0 (0.5) | 79.8 (0.5) |
Kappa | 0.800 | 0.770 (0.013) | 0.652 (0.020) | 0.773 (0.014) | 0.651 (0.010) | 0.764 (0.010) | 0.636 (0.011) |
Abbreviations: DCCN-A, deep convolutional neural network, algorithm A; DCCN-U, deep convolutional neural network, algorithm U; H, human; NS, no stereo; NSG, no stereo gradable; NPV, negative predicted value; PPV, positive predicted value; WS, with stereo pairs..
All values indicate percentages, except for the kappa coefficient. Values in parentheses indicate standard deviations.