Enhancing Cardiovascular Disease Prediction through Multi-Modal Self-Supervised Learning

This is the official implementation of our paper "Enhancing Cardiovascular Disease Prediction through Multi-Modal Self-Supervised Learning" (2024).

If you find the code useful, please cite

@inproceedings{girlanda2024enhancing,
  title={Enhancing Cardiovascular Disease Prediction through Multi-Modal Self-Supervised Learning},
  author={Girlanda, Francesco and Demler, Olga and Menze, Bjoern and Davoudi, Neda},
  booktitle={BMVC},
  year={2024}
}

Instructions

MAE

MMSSL

We used Python 3.11.6 to run our code. To set up a virtual environment and install the Python dependencies listed in the requirements.txt file, follow these steps:

1. Open a terminal or command prompt and create a new virtual environment using venv:

python3 -m venv venv

2. Activate the virtual environment:

source venv/bin/activate

3. Install the required Python packages using pip:

pip install -r requirements.txt

4. You are now ready to use the code and run the project. Set up the configuration in the config folder and then run the main file:

python run.py