Summary
Categorizes forms and sources of bias in healthcare AI, identifies where bias can enter throughout the data lifecycle, and recommends data-management and risk-management practices to identify and mitigate it.
Healthcare Implications
Gives healthcare AI developers, risk managers, providers, and regulators a consensus standard for incorporating bias assessment and mitigation into data governance and system development.