So, what is it about?
My proposed approach integrates a CNN–LSTM hybrid model for ECG classification. The CNN layers will first extract local morphological features from the ECG signals, and the LSTM layers will then capture the temporal dependencies across heartbeats for improved classification accuracy. This aims to enhance both feature representation and sequential learning compared to a standalone LSTM model.
Code of Conduct
So, what is it about?
My proposed approach integrates a CNN–LSTM hybrid model for ECG classification. The CNN layers will first extract local morphological features from the ECG signals, and the LSTM layers will then capture the temporal dependencies across heartbeats for improved classification accuracy. This aims to enhance both feature representation and sequential learning compared to a standalone LSTM model.
Code of Conduct