During the Mozfest 90 minute session, participants were invited to interact with 8 posters inspired in the Matrix red pill blue pill analogy. In each poster, the blue pill contained information on the advantages that artificial intelligence, machine learning and open datasets offer to healthcare, and the red pills contained less talked about but very crucial facts that prevent us from seeing the real benefits of healthcare applied technologies.
The 25 session participants shared their thoughts, ideas and questions in the form of post-its, that were later discussed and implemented as session learnings that are now distributed as issues on this repository.
We divided participant collaborations in two main groups:
Design thinking questions heavily inspired in OpenCon’s do-a-thon challenges. Possible solutions, recommendations and routes of actions.
You can read about our learnings and submit your questions, challenges and solutions in the issues section of the repo. We invite session participants, and anyone interested to keep the conversation going. The end goal of this project is to share our learnings and findings with fellow researchers, institutions, or anyone interested in working towards making science more open.
You can also access the session participant’s thoughts on each poster and add your own here. We highly encourage you to add your ideas, our project would be nothing without participants like yourself!
To continue the discussion, the session has a new home on Github . The goal of this repository is to serve as a channel to:
- Raise awareness on the underrepresentation of minorities in health datasets, as the lack of available data about certain communities affects AI algorithm accountability, thus its impact on global health.
- Discuss how balanced healthcare datasets might help us develop more accurate diagnostic tools as well as avoid discrimination and inequality in healthcare.
This repository serves as a space to collaborate towards the implementation of better practices to address the class imbalance problem in healthcare datasets, and contains session notes, materials and resources used in the session, and learnings and future ideas in the form of github issues.
All session materials are safely preserved in Zenodo, you can download them here.
Want to contribute?
This repository is the end product of collaboration between session attendees, participants, and people interested in the project who could not attend the live session.
We are seeking contributors to help us expand ideas in github issues. If anything you’ve read seems interesting to you, we invite you to contribute by commenting on existing issues, or creating new ones.
If you contributed, let us know here. If you were in the Mozfest session, write your name here for us to credit you.
If you want to keep up to date with the repo, please consider subscribing to issues you consider interesting.