To create and activate the environment.
conda env create -f environment.yml
conda activate websmsreg
To export the conda environment to Jupyter Notebook.
python -m ipykernel install --user --name=websmsreg
The data can be collected from Swedish MS REGistry (SMSREG). The data shall be kept in a designated folder. The path to the data can be provided in the notebook (data_cleaning_and_splitting.ipynb) under the input section.
Code for training and evaluation of both the model and conformal prediction is given in notebook (random_forest_cp.ipynb)
The model and scripts used for the website model are available in the folder gradio.
To run the website locally, activate the conda environment and run
python3 gradio/app.py
Please cite:
Conformal prediction enables disease course prediction and allows individualized diagnostic uncertainty in multiple sclerosis
Akshai Parakkal Sreenivasan, Aina Vaivade, Yassine Noui, Payam Emami Khoonsari, Joachim Burman, Ola Spjuth, Kim Kultima*
Status: Submitted.