This project digitizes raw ECG signals, preprocesses them, and applies deep learning models for heartbeat classification and cardiac risk prediction. It includes data acquisition, feature extraction, neural network training, and real-time monitoring. The system aims to detect arrhythmias early and support clinical decision-making with high accuracy.
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