Table 3.
Precision | Recall | Accuracy | F1-score | AUC | AUPR | |
---|---|---|---|---|---|---|
EfficientNetV2 | 0.5077 | 0.9015 | 0.6231 | 0.6495 | 0.7800 | 0.6649 |
ResNet | 0.9786 | 0.9602 | 0.9764 | 0.9693 | 0.9960 | 0.9943 |
Vision transformer | 0.9811 | 0.9769 | 0.9838 | 0.9790 | 0.9982 | 0.9975 |
DeepDSR | 0.9833 | 0.9895 | 0.9894 | 0.9864 | 0.9991 | 0.9986 |
The bold fonts represent the best performance in each column.