Research Article
Optimal Deep-Learning-Enabled Intelligent Decision Support System for SARS-CoV-2 Classification
Table 1
Result analysis of EDLFM-SI model with distinct measures under data set-1.
| No. of runs | Precision | Sensitivity | Specificity | Accuracy | F-score |
| Run-1 | 0.9872 | 0.9856 | 0.9870 | 0.9863 | 0.9864 | Run-2 | 0.9888 | 0.9904 | 0.9886 | 0.9895 | 0.9896 | Run-3 | 0.9880 | 0.9880 | 0.9878 | 0.9879 | 0.9880 | Run-4 | 0.9873 | 0.9912 | 0.9870 | 0.9891 | 0.9892 | Run-5 | 0.9881 | 0.9920 | 0.9878 | 0.9899 | 0.9900 | Run-6 | 0.9888 | 0.9880 | 0.9886 | 0.9883 | 0.9884 | Run-7 | 0.9864 | 0.9864 | 0.9862 | 0.9863 | 0.9864 | Run-8 | 0.9880 | 0.9872 | 0.9878 | 0.9875 | 0.9876 | Run-9 | 0.9904 | 0.9872 | 0.9902 | 0.9887 | 0.9888 | Run-10 | 0.9904 | 0.9888 | 0.9902 | 0.9895 | 0.9896 | Average | 0.9883 | 0.9885 | 0.9881 | 0.9883 | 0.9884 |
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