Abstract
—As artificial intelligence (AI) systems increasingly become popular in the healthcare sector, it is important to ensure the output of these technologies is fair and bias-free. This paper provides a concise survey of fairness metrics applied in healthcare AI, including their mathematical representations, suitable use cases, and limitations, which are lacking in the existing literature. The study also highlights the significance of implementing fairness metrics to ensure equitable outcomes across diverse patient populations and discusses the challenges and future directions in this rapidly evolving field.