Table 3.
Quantitative performance results of evaluation metrics for state-of-the-art algorithms for the binary COVID-19 dataset. The best results among different classifiers are shown by bold black fonts.
| Metric | MobileNet | DesnseNet121 | InceptionV3 | ResNet50 | VGG16 | ResNet50V2 | ResNet152V2 | nCOVnet | CTnet-10 | Proposed | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| ACC |
AVG | 0.888252 | 0.882521 | 0.902579 | 0.836676 | 0.885387 | 0.785111 | 0.908309 | 0.896731 | 0.886574 | 0.988539 |
| STD | 0.008435 | 0.009437 | 0.007891 | 0.040947 | 0.018467 | 0.047282 | 0.056214 | 0.043103 | 0.032791 | 0.006189 | |
| Best | 0.901883 | 0.903922 | 0.913226 | 0.893533 | 0.905344 | 0.826711 | 0.948979 | 0.936001 | 0.924471 | 0.990218 | |
| Worst |
0.865554 |
0.869047 |
0.879011 |
0.803216 |
0.827056 |
0.748022 |
0.853432 |
0.842854 |
0.832498 |
0.983337 |
|
| Precision |
AVG | 0.852459 | 0.950355 | 0.848958 | 0.930233 | 0.890244 | 0.854962 | 0.914634 | 0.904323 | 0.894084 | 0.988095 |
| STD | 0.046995 | 0.009899 | 0.042101 | 0.030749 | 0.033152 | 0.042653 | 0.110804 | 0.100705 | 0.090687 | 0.002934 | |
| Best | 0.883007 | 0.965652 | 0.858922 | 0.954767 | 0.915038 | 0.884578 | 0.937876 | 0.927388 | 0.917053 | 0.989778 | |
| Worst |
0.815561 |
0.937689 |
0.803574 |
0.874521 |
0.854538 |
0.821366 |
0.794022 |
0.782444 |
0.770778 |
0.984971 |
|
| Recall |
AVG | 0.928571 | 0.797619 | 0.970238 | 0.714286 | 0.869048 | 0.666667 | 0.892857 | 0.881279 | 0.869121 | 0.988095 |
| STD | 0.009231 | 0.073547 | 0.000213 | 0.086395 | 0.027655 | 0.069103 | 0.090967 | 0.078957 | 0.066918 | 0.010117 | |
| Best | 0.928895 | 0.814423 | 0.978845 | 0.786454 | 0.891044 | 0.736754 | 0.952612 | 0.943496 | 0.933685 | 0.991309 | |
| Worst |
0.897554 |
0.730567 |
0.966328 |
0.659113 |
0.837529 |
0.608932 |
0.811042 |
0.797931 |
0.785092 |
0.985677 |
|
| F-measure |
AVG | 0.888889 | 0.867314 | 0.905556 | 0.808081 | 0.879518 | 0.749164 | 0.903614 | 0.892503 | 0.880941 | 0.988095 |
| STD | 0.015655 | 0.027781 | 0.008944 | 0.053299 | 0.037424 | 0.061454 | 0.046513 | 0.037597 | 0.028482 | 0.006526 | |
| Best | 0.900767 | 0.893563 | 0.922155 | 0.846568 | 0.899045 | 0.795423 | 0.939082 | 0.929966 | 0.920728 | 0.993044 | |
| Worst |
0.841911 |
0.789022 |
0.899294 |
0.748989 |
0.845652 |
0.681921 |
0.857939 |
0.847628 |
0.837406 |
0.979663 |
|
| AUC | AVG | 0.889711 | 0.879473 | 0.905009 | 0.832281 | 0.884836 | 0.780847 | 0.907755 | 0.896839 | 0.885949 | 0.988523 |
| STD | 0.010494 | 0.011373 | 0.009879 | 0.042439 | 0.035194 | 0.048984 | 0.053612 | 0.043531 | 0.031866 | 0.006332 | |
| Best | 0.910898 | 0.893315 | 0.921883 | 0.868494 | 0.908935 | 0.834326 | 0.943089 | 0.925978 | 0.908786 | 0.989446 | |
| Worst | 0.875497 | 0.869454 | 0.883533 | 0.773545 | 0.867435 | 0.738782 | 0.854025 | 0.841809 | 0.828476 | 0.981088 |