Table 14.
Comparison of different deep networks for classification of Normal, MI, CAD, and CHF.
| Model | Intra-Patient | Inter-Patient | ||||||
|---|---|---|---|---|---|---|---|---|
| ACC (%) | PPV (%) | SEN (%) | SPE (%) | ACC (%) | PPV (%) | SEN (%) | SPE (%) | |
| VGG_16 [30] | 99.84 | 99.62 | 99.44 | 99.89 | 79.63 | 64.03 | 56.65 | 85.83 |
| ResNet_18 [33] | 99.79 | 99.44 | 99.24 | 99.85 | 91.27 | 80.21 | 75.72 | 93.26 |
| ResNet_34 [33] | 99.79 | 99.52 | 99.18 | 99.85 | 91.99 | 81.47 | 77.15 | 93.78 |
| ResNet_50 [33] | 99.72 | 99.25 | 99.12 | 99.80 | 89.76 | 75.63 | 76.08 | 92.58 |
| DenseNet | 99.63 | 99.20 | 98.86 | 99.73 | 93.97 | 87.78 | 81.77 | 95.24 |
| Proposed | 99.74 | 99.09 | 98.67 | 99.83 | 96.92 | 92.17 | 89.18 | 97.77 |