Table 16.
Results of models trained on COVID-19 Image Data Collection and COVID-19 CT & Radiograph Image Data Stock on an additional test set.
| Precision | Recall | F1 score | Accuracy | Binary AUC | |
|---|---|---|---|---|---|
| COVID-19 Image Data Collection | |||||
| ResNet-18 | 0.52 | 0.92 | 0.67 | 0.54 | 0.54 |
| ResNet-50 | 0.50 | 1.00 | 0.67 | 0.50 | 0.50 |
| DenseNet-169 | 0.00 | 0.00 | 0.00 | 0.50 | 0.50 |
| WideResNet-50 | 0.00 | 0.00 | 0.00 | 0.38 | 0.38 |
| DenseNet-121+ |
0.50 |
1.00 |
0.67 |
0.50 |
0.50 |
| COVID-19 CT & Radiograph Image Data Stock binary | |||||
| ResNet-18 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
| ResNet-50 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
| DenseNet-169 | 1.00 | 0.92 | 0.96 | 0.96 | 0.96 |
| WideResNet-50 | 1.00 | 1.00 | 1.00 | 1.00 | 1.00 |
| DenseNet-121+ |
0.86 |
1.00 |
0.92 |
0.92 |
0.92 |
| COVID-19 CT & Radiograph Image Data Stock multiclass | |||||
| ResNet-18 | 1.00 | 1.00 | 1.00 | 0.71 | 1.00 |
| ResNet-50 | 1.00 | 1.00 | 1.00 | 0.71 | 1.00 |
| DenseNet-169 | 1.00 | 1.00 | 1.00 | 0.71 | 1.00 |
| WideResNet-50 | 1.00 | 1.00 | 1.00 | 0.75 | 1.00 |
| DenseNet-121+ | 0.91 | 0.83 | 0.87 | 0.54 | 0.87 |