Research Article
[Retracted] A Rapid Artificial Intelligence-Based Computer-Aided Diagnosis System for COVID-19 Classification from CT Images
Table 2
Classification output of the proposed method using ResNet50 and EFA.
| Classifier | Recall rate (%) | Precision rate (%) | FNR (%) | AUC | Accuracy (%) | Time (sec) |
| Linear SVM | 95.96 | 96.06 | 3.04 | 0.993 | 96.0 | 95.626 | Quadratic SVM | 96.93 | 97 | 3.07 | 0.996 | 96.9 | 107.41 | Cubic SVM | 97.20 | 97.23 | 2.8 | 1 | 97.2 | 121.81 | Medium Gaussian SVM | 95.0 | 95.0 | 5.0 | 0.993 | 95.0 | 140.97 | Fine KNN | 93.03 | 93.13 | 6.97 | 0.95 | 93.1 | 143.19 | Medium KNN | 89.9 | 90.86 | 10.1 | 0.98 | 89.9 | 151.14 | Cosine KNN | 93.36 | 93.33 | 6.64 | 0.986 | 93.4 | 162.94 | Cubic KNN | 89.9 | 90.43 | 10.1 | 0.976 | 89.9 | 609.23 | Weighted SVM | 89.76 | 91.1 | 10.24 | 8.986 | 89.8 | 178.37 | Subspace KNN | 94.13 | 94.1 | 5.87 | 0.986 | 94.1 | 440.78 |
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