The Data Artifacts Glossary: a community-based repository for bias on health datasets.

ABSTRACT:

Background

The deployment of Artificial Intelligence (AI) in healthcare has the potential to transform patient care through improved diagnostics, personalized treatment plans, and more efficient resource management. However, the effectiveness and fairness of AI are critically dependent on the data it learns from. Biased datasets can lead to AI outputs that perpetuate disparities, particularly affecting social minorities and marginalized groups.

Objective

This paper introduces the "Data Artifacts Glossary", a dynamic, open-source framework designed to systematically document and update potential biases in healthcare datasets. The aim is to provide a comprehensive tool that enhances the transparency and accuracy of AI applications in healthcare and contributes to understanding

SUBMITTER: Gameiro RR 

PROVIDER: S-EPMC11792693 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature