Table 5.
Results (%) comparison between the proposed CAD framework and other related studies based on SARS-COV-2 CT scan dataset.
| Article | Method | SP | SE | Acc | Precision | F1-score |
|---|---|---|---|---|---|---|
| 75 | Customized CNN | - | 96 | 95 | - | 95 |
| 23 | CoviDenseNet | 85.92 | 87.41 | 86.88 | 85.92 | 89.53 |
| 21 | x-DNN3 | - | 95.53 | 97.38 | - | 97.31 |
| 76 | Customized Simple CNN | 95.56 | 96 | 95.78 | 95.56 | - |
| 22 | Bi-LSTM | - | 98.87 | 98.37 | - | 98.14 |
| 77 | VGG-16 + ResNet-50 + Xception + Majority voting | 98.79 | 98.79 | 98.79 | 98.79 | 98.79 |
| 78 | Fuzzy Ranking + VGG-11, ResNet-50-2, and Inception v3 | 99 | 99.08 | 98.93 | 99 | 98.93 |
| 79 | Customized CNN + Genetic Algorithm + Xboost | - | 99 | 99 | - | 99 |
| 33 | ResNet18 + ShuffleNet + AlexNet + GoogleNet + DWT + GLCM + Statistical features + PCA + SVM | 99 | 99 | 99 | 99 | 99 |
| Proposed CAD framework | 99.72 | 99.47 | 99.60 | 99.72 | 99.60 | |
Bi-LSTM: bidirectional long short-term memory; CT: computed tomography; CNN: convolutional neural network; CAD: computer-assisted diagnostic; DWT: discrete wavelet transform; GLCM: gray-level covariance matrix; PCA: principal component analysis; SVM: support vector machine; SARS-CoV-2: severe respiratory syndrome coronavirus 2.