Chalmers and ETHZ Masters Thesis: Learning Interpretable Prototype Trajectories for Patients with Alzheimer's Disease

• OS: Linux (not tested on other OSs)
• Python 3.7 or higher
• PyTorch version which is compatible with your setup

• Data from the ADNI dataset, specifically the TADPOLE challenge dataset (http://adni.loni.usc.edu/)

To install the all dependencies needed for this project to run please run the following commands. The first command can be skipped if the repository was restored from an archive.

# Clone the project
git clone [email protected]:sarah-mdv/LIPTraAD.git
# Change into project directory
cd LIPTraAD
# Create a virtual environment
python -m venv venv
# Activate it venv
source venv/bin/activate
# Upgrade pip
pip install --upgrade pip
# Install requirements
pip install -r requirements
# Install the project
pip install -e .
# Install PyTorch. Version may be adjusted based on your local setup (GPU, driver versions, etc)
# check: https://pytorch.org/
pip install torch