Skip to main content
. 2017 Nov 9;135(11):1170–1176. doi: 10.1001/jamaophthalmol.2017.3782

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..

a

All values indicate percentages, except for the kappa coefficient. Values in parentheses indicate standard deviations.