Table 7 Comparison with existing techniques.
From: Artificial intelligence framework for heart disease classification from audio signals
Ref. | Model/Features | Testing Accuracy | Precision | Recall | F1-score |
|---|---|---|---|---|---|
CNN with Wavelet-based Features | 82.22% | – | – | – | |
SVM with MFCC Features | 85.36% | – | – | – | |
KNN with MFCC Features | 84.53% | – | – | – | |
CNN with MFSC Features | 88.18% | – | – | – | |
CNN with MFSC Features | 93.88% | – | – | – | |
Proposed | MLP with MFCC Features Vector | 95.65% | 96.60% | 97.60% | 96.60% |
