Contributing to this toolbox

We welcome all contributions that help us achieve our aim of speeding up Machine Learning (ML) / AI research in health and life sciences.

Examples of contributions are

  • Data loaders for specific health & life sciences data

  • Network architectures and components for deep learning models

  • Tools to analyze and/or visualize data

  • Bug reports

  • Documentation improvements, including fixing typos

  • Suggestions about codebase improvements

All contributions to the toolbox need to come with unit tests, and will be reviewed when a pull request is started. If in doubt, reach out to the core hi-ml team before starting your work.

Please look through the existing folder structure to find a good home for your contribution.

For a full set of design and guidelines, please check our coding guidelines documentation.