Artificial Intelligence to Promote Racial and Ethnic Cardiovascular Health Equity.

Abstract

Purpose of review: The integration of artificial intelligence (AI) in medicine holds promise for transformative advancements aimed at improving healthcare outcomes. Amidst this promise, AI has been envisioned as a tool to detect and mitigate racial and ethnic inequity known to plague current cardiovascular care. However, this enthusiasm is dampened by the recognition that AI itself can harbor and propagate biases, necessitating a careful approach to ensure equity. This review highlights topics in the landscape of AI in cardiology, its role in identifying and addressing healthcare inequities, promoting diversity in research, concerns surrounding its applications, and proposed strategies for fostering equitable utilization.

Recent findings: Artificial intelligence has proven to be a valuable tool for clinicians in diagnosing and mitigating racial and ethnic inequities in cardiology, as well as the promotion of diversity in research. This promise is counterbalanced by the cautionary reality that AI can inadvertently perpetuate existent biases stemming from limited diversity in training data, inherent biases within datasets, and inadequate bias detection and monitoring mechanisms. Recognizing these concerns, experts emphasize the need for rigorous efforts to address these limitations in the development and deployment of AI within medicine.

Summary: Implementing AI in cardiovascular care to identify and address racial and ethnic inequities requires careful design and execution, beginning with meticulous data collection and a thorough review of training datasets. Furthermore, ensuring equitable performance involves rigorous testing and continuous surveillance of algorithms. Lastly, the promotion of diversity in the AI workforce and engagement of stakeholders are crucial to the advancement of equity to ultimately realize the potential for artificial intelligence for cardiovascular health equity.