Table 9 Performance comparison of different CNN models with the proposed IDLHICNet model.
Datasets | Model | Accuracy (%) | Precision (%) | Recall (%) | F1-score (%) |
|---|---|---|---|---|---|
Faisalabad | Standard CNN | 92.85 | 91.45 | 90.12 | 90.78 |
1D-CNN | 94.1 | 93.75 | 92.6 | 93.17 | |
ResNet-18 | 95.34 | 94.28 | 94.1 | 94.19 | |
VGG-16 | 94.55 | 93.2 | 92.48 | 92.84 | |
CNN-LSTM | 95.6 | 95.12 | 94.9 | 95.01 | |
Proposed (IDLHICNet) | 99.51 | 99.5 | 99.5 | 99 | |
CVD | Standard CNN | 91.7 | 91 | 90.12 | 90.55 |
1D-CNN | 93.2 | 92.8 | 92 | 92.4 | |
ResNet-18 | 94.4 | 93.45 | 93.1 | 93.27 | |
VGG-16 | 93.6 | 92 | 91.5 | 91.75 | |
CNN-LSTM | 94.8 | 94.1 | 93.6 | 93.85 | |
Proposed (IDLHICNet) | 98.76 | 98.5 | 98.5 | 99 | |
Heart Failure | Standard CNN | 89.45 | 88.5 | 88.1 | 88.3 |
1D-CNN | 91.35 | 90.8 | 90.4 | 90.6 | |
ResNet-18 | 92.85 | 92 | 91.5 | 91.75 | |
VGG-16 | 91.2 | 90.3 | 89.9 | 90.1 | |
CNN-LSTM | 93.8 | 93.1 | 92.9 | 93 | |
Proposed (IDLHICNet) | 99.07 | 99.14 | 99.05 | 99.22 |
