Research Article
COVID-19 Classification from Chest X-Ray Images: A Framework of Deep Explainable Artificial Intelligence
Table 3
Proposed framework COVID-19 classification results on Covid-GAN and Covid-Net mini Chest X-ray dataset.
| Classifiers | Features | Measures | EffNet | VGG16 | SL EffNet | SL VGG16 | Proposed | Accuracy (%) | Time (%) |
| Softmax | ✓ | | | | | 91.6 | 91.4534 | | ✓ | | | | 89.4 | 94.3423 | | | ✓ | | | 94.8 | 62.2322 | | | | ✓ | | 93.5 | 64.5454 | | | | | ✓ | 97.2 | 47.6654 |
| Naïve Bayes | ✓ | | | | | 90.1 | 85.3843 | | ✓ | | | | 87.5 | 78.6434 | | | ✓ | | | 92.2 | 51.5444 | | | | ✓ | | 90.9 | 49.9845 | | | | | ✓ | 94.6 | 41.9905 |
| MCSVM | ✓ | | | | | 90.6 | 82.5645 | | ✓ | | | | 90.1 | 78.9964 | | | ✓ | | | 94.2 | 59.4354 | | | | ✓ | | 92.9 | 64.8634 | | | | | ✓ | 96.9 | 48.6654 |
| ELM | ✓ | | | | | 93.3 | 71.5535 | | ✓ | | | | 89.2 | 69.6543 | | | ✓ | | | 95.8 | 52.5454 | | | | ✓ | | 95.9 | 47.6543 | | | | | ✓ | 98.2 | 39.6652 |
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