Table 8.
A comparison between ECG-BiCoNEt and other relevant studies.
| Binary classification | |||||
|---|---|---|---|---|---|
| Reference | Method | Sensitivity (%) | Precision (%) | Specificity (%) | Accuracy (%) |
| [65] | hexaxial feature mapping + GLCM + CNN | 0.984 | 0.943 | 0.94 | 96.2 |
| [64] | ResNet-18 | 0.986 | 0.985 | 0.96 | 98.62 |
| Proposed ECG-BiCoNet |
Pooling features after DWT + Fully connected Features + SU + MCS |
0.988 |
0.988 |
0.988 |
98.80 |
| Multiclass Classification | |||||
| Sensitivity (%) |
Precision (%) |
Specificity (%) |
Accuracy (%) |
||
| [63] | EfficientNet | 0.758 | 0.808 | – | 81.8 |
| [64] | MobileNet | 0.908 | 0.913 | 0.928 | 90.79 |
| Proposed ECG-BiCoNet | Pooling features after DWT + Fully connected Features + SU + MCS | 0.917 | 0.919 | 0.959 | 91.73 |