Key result
Hybrid CNN-Vision Transformer framework achieves ~99% accuracy in detecting cardiac diseases from ECG signals.
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A hybrid deep learning framework combining CNN, Vision Transformer, and Whale Optimization Algorithm improves the automated classification of cardiac diseases from ECG signals.
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Lavanya et al. (2026) studied Cardiac diseases. Hybrid CNN-ViT model with Whale Optimization Algorithm vs. Conventional machine learning techniques was evaluated on Classification accuracy. The proposed Hybrid Optimized Framework utilizing CNN, Vision Transformer, and Whale Optimization Algorithm achieved 98.76% accuracy in detecting and classifying cardiac diseases from ECG signals.
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