Table 1. Comparison of diagnostic performance for each Convolutional Neural Network (CNN) model.

CNN model	Accuracy	Sensitivity	Specificity	Precision	F1-Score
ResNet50	0.810 ± 0.046	0.764 ± 0.088	0.889 ± 0.046	0.780 ± 0.059	0.800 ± 0.045
Inception v3	0.821 ± 0.029	0.778 ± 0.087	0.892 ± 0.035	0.786 ± 0.054	0.778 ± 0.054
EfficientNet-b1	0.835 ± 0.054	0.784 ± 0.074	0.896 ± 0.033	0.809 ± 0.082	0.794 ± 0.067
EfficientNet-b2	0.853 ± 0.050	0.822 ± 0.087	0.912 ± 0.034	0.829 ± 0.089	0.822 ± 0.065
EfficientNet-b3	0.842 ± 0.040	0.787 ± 0.090	0.900 ± 0.036	0.818 ± 0.088	0.797 ± 0.068

The values are given as the mean and the standard deviation by 5-fold cross validation.