Table 3. The screening performance of different base models. Date represents mean (95% confidence interval).

Model	AUC	Accuracy	Precision	Sensitivity	Specificity
VGGNet	0.83 [0.79, 0.87]	0.75 [0.72, 0.78]	0.76 [0.66, 0.86]	0.77 [0.71, 0.83]	0.76 [0.70, 0.82]
GoogLeNet	0.84 [0.80, 0.88]	0.77 [0.76, 0.78]	0.78 [0.72, 0.84]	0.79 [0.75, 0.83]	0.77 [0.74, 0.80]
ResNet	0.89 [0.86, 0.92]	0.82 [0.80, 0.84]	0.81 [0.73, 0.89]	0.85 [0.79, 0.91]	0.82 [0.76, 0.88]
ResNet+C	0.94 [0.91, 0.97]	0.86 [0.84, 0.88]	0.85 [0.76, 0.94]	0.89 [0.83, 0.95]	0.86 [0.79, 0.93]
Dentists	–	0.79 [0.75, 0.83]	0.81 [0.80, 0.82]	0.84 [0.83, 0.85]	0.73 [0.71, 0.75]

AUC, the area under the ROC (receiver operating characteristic) curve.