Cardiovascular Disease Classification on publicly available database of heart sounds
98.95Accuracy1D+2D CNN-LSTM
Evaluation Results
| Method | Links | |
|---|---|---|
| 1D+2D CNN-LSTMFeatures=Gabor dictionary (β = 2^1) + elastic net (α = 0.1), Classifier=1D+2D CNN-LSTM, Training=ADAM2026.04 | 98.95 | |
| Light 1D CNN-LSTMFeatures=VMD + weighted logarithmic, Classifier=Light 1D CNN-LSTM, Training=SGDM2026.04 | 98.65 | |
| Deep 2D CNN-LSTMFeatures=Raw PCG signals, Classifier=Deep 2D CNN-LSTM, Training=ADAM2026.04 | 98.48 | |
| 1D CNN-LSTMFeatures=Gabor dictionary (β = 2^1) + elastic net (α = 0), Classifier=1D CNN-LSTM, Training=SGDM2026.04 | 98.39 | |
| 1D+2D CNN-LSTMFeatures=Gabor dictionary (β = 2^1) + elastic net (α = 0.1), Classifier=1D+2D CNN-LSTM, Training=SGDM2026.04 | 98.14 | |
| 1D CNN-LSTMFeatures=Gabor dictionary (β = 2^1) + elastic net (α = 0.1), Classifier=1D CNN-LSTM, Training=ADAM2026.04 | 97.97 | |
| Deep 2D CNN-LSTMFeatures=Transformed PCG signals, Classifier=Deep 2D CNN-LSTM, Training=ADAM2026.04 | 95.4 |