0.68
|
-
|
-
|
-
|
-
|
0.74
|
0.63
|
0.69
|
|
[10]
|
DualCheXNet
|
-
|
-
|
-
|
-
|
-
|
-
|
0.823
|
-
|
-
|
|
[2]
|
CNN
|
0.9240
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
|
BPNN
|
0.8004
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
|
CpNN
|
0.8957
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
|
[8]
|
U-Net
|
0.94
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
-
|
|
[47]
|
Ensemble CNN
|
|
|
|
|
|
|
0.940
|
|
|
|
[51]
|
STN based CNN
|
0.96
|
0.651
|
-
|
-
|
-
|
-
|
-
|
0.60
|
0.70
|
|
[46]
|
Ensemble with AlexNet
|
0.862
|
|
|
|
|
|
0.925
|
|
|
|
[26]
|
FHRNet
|
-
|
-
|
-
|
-
|
-
|
-
|
0.812
|
-
|
-
|
|
[20]
|
AG-CNN
|
-
|
-
|
-
|
-
|
-
|
-
|
0.871
|
-
|
-
|
|
[28]
|
Ensemble DCNN (for Cardiomegaly)
|
0.93
|
-
|
92.00
|
94.00
|
-
|
-
|
0.97
|
-
|
-
|
|
Ensemble DCNN (for Tuberculosis)
|
0.90
|
-
|
92.00
|
88.00
|
-
|
-
|
0.94
|
-
|
-
|
|
[41]
|
MA-DCNN
|
-
|
-
|
-
|
-
|
-
|
-
|
0.794
|
-
|
-
|
|
[5]
|
ChestNet
|
0.932
|
-
|
-
|
97.13
|
85.85
|
-
|
0.984
|
-
|
-
|
|
[46] CNN
|
Maryland (MC) dataset
|
0.79
|
-
|
-
|
-
|
-
|
-
|
0.811
|
-
|
-
|
|
Shenzhen (SZ)
|
0.844
|
-
|
-
|
-
|
-
|
-
|
0.900
|
-
|
-
|
|
Combined (CB)
|
0.862
|
-
|
-
|
-
|
|
