This study tackles the ECG classification problem by means of a methodology, which is able to enhance classification performance while simultaneously reducing the computational resources, making it ...

In this study, we developed and evaluated a DL-based model that has a feature extraction stage, an ECG-lead subset selection stage and a decision-making stage to automatically interpret multiple ...

Keywords: feature extraction, variational autoencoder, ECG, electrocardiography, deep learning, explainable AI Citation: Kuznetsov VV, Moskalenko VA, Gribanov DV and Zolotykh NY (2021) Interpretable ...

We propose a method for generating an electrocardiogram (ECG) signal for one cardiac cycle using a variational autoencoder. Our goal was to encode the original ECG signal using as few features as ...

Left Ventricular Hypertrophy (LVI) diagnosis using Machine Learning methods (K-means and KNN) and feature extraction techniques of electrocardiogram (ECG) signals.

This notebook illustrates feature selection reverting many of the selection method results into pandas dataframes so that you get the appropriate column headings. - GitHub - ...