This repository contains Jupyter Notebooks and associated data that explores using machine learning models to predict disease between JIA (Juvenile Idiopathic Arthritis), J-IBD (Juvenile Inflammatory Bowel Disease) and healthy controls, and investigate the drivers of prediction in the model.
The Jupyer Notebooks were created using Visual Studio Code (v1.89.1), with Python v3.9.13 and the Jupyter notebook extension in VS Code.
If you do not have an instance of Python and Jupyter Notebook, either
- install Visual Studio Code from https://code.visualstudio.com/, and then add the Python and Juptyer Notebook extensions. Would also suggest installing the Data Wrangler extension.
or
- download Anaconda from https://www.anaconda.com/download for your operating system.
In order to run the notebook you will also need to install the libraries sklearn, xgboost and shap.
To do this use the line command in terminal for Mac or Windows Terminal for Windows PC. You can use pip to install the three libraries: pip install sklearn pip install xgboost pip install shap
For more information for installations https://scikit-learn.org/stable/install.html https://xgboost.readthedocs.io/en/stable/install.html https://pypi.org/project/shap/
Download the notebooks and the data folder and open the notebook in your preferred Jupyter Notebook platform