ahart97 / ecg_diagnosis

ECG Diagnosis

Project Title: Automatic ECG Diagnosis

Description

This repository contains a Python implementation for automatic ECG diagnosis using machine learning algorithms in scikit-learn and TensorFlow. The code is based on the work done by Ribeiro et al.. The purpose of this repository is to provide an easy-to-use and customizable implementation for ECG diagnosis, making use of the latest advancements in machine learning.

Installation

To use this repository, you will need to have the following packages installed:

Python 3

• NumPy
• Pandas
• scikit-learn
• TensorFlow
• h5py
• xmljson
• scipy
• tqdm
• xarray
• seaborn
• openpyxl
• neurokit2
• matplotlib

You can install these packages using pip or another package manager.

Usage

• All the code is in one Jupyter notebook with comments
• The data folder holds all of the data needed to run the code
• The outputs folder has all of the outputs generated with running the code
• The models folder has all of the models used in the code

Contributing

If you would like to contribute to this repository, please fork the repository and make the necessary changes. Then, submit a pull request for review.