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ECG Federated Learning

Overview

This project implements Federated Learning for ECG signal classification using the PhysioNet/CinC Challenge 2017 dataset. The objective is to categorize ECG signals into three classes: Normal, Atrial Fibrillation, and Other.

Environment

  • OS: Linux Mint 22
  • Python: 3.11.11

How to run.

  1. Download the dataset.

    bash download_dataset.sh
  2. Install dependencies.

    pip install -r requirements.txt
  3. Login to Wandb.

    Choose one of the following methods:

    • Via command line.
      wandb login
    • Using .env file.
      echo "WANDB_API_KEY=your_wandb_api_key" > .env
    • Using environment variable.
      export WANDB_API_KEY=your_wandb_api_key

    If you prefer not to use Wandb (not recommended), you can disable it:

    • Using .env file.
      echo "WANDB_MODE=disabled" > .env
    • Using environment variable.
      export WANDB_MODE=disabled
  4. Run the following .ipynb files in the order:

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