NIH NCATS Bias Detection Tools for Clinical Decision Making

Background

The National Center for Advancing Translational Sciences (NCATS) launched the Bias Detection Tools for Clinical Decision Making Challenge in October 2022. The challenge awarded a combined total of $700,000 to those teams best able to make an open-source solution that detects and mitigates bias in AI/ML models used in healthcare settings. Over 200 individuals registered to compete in this Challenge, and the resources/webinars provided during the course of the Challenge aimed to provide context and cross-training for a complex issue that encompasses AI/ML, healthcare and bias/ethics. The goal of this challenge was to create solutions and share these open-source tools with the community so that the solutions will be enhanced, augmented, integrated, and, optimally, implemented into healthcare systems.

As part of NCATS’ mission to foster sustainable community engagement, sharing, and progress in this space, all outputs (submissions & documentation) are shared back to the community in this repository. Our goal is to further build out our tool-box for making AI/ML unbiased and fair for all subsets of populations; and provide a space for these solutions to allow iteration by stakeholders and to further exhibit and validate the robustness required of these types of tools.

This repository memorializes submissions from the winning teams, honorable mentions, and challengers. The outline below documents each challenger's code and video submission, provides a link back to the original repository, and displays their videos. Additional resources can be found in the resources folder.