AI has been seen as a tool that could help detect and reduce the racial and ethnic inequities that persist in cardiovascular care. However, AI can also carry and spread biases of its own, which means it must be approached with care. This review looks at the role of AI in cardiology in identifying and addressing these inequities, and in promoting diversity in research, as well as the concerns its use raises and strategies for using it fairly.
The authors describe how AI has already helped reduce some inequities. In one study, an AI tool identified patients with severe heart valve disease and alerted their doctors, improving follow-up care for patients of all races. Even so, Black patients still faced greater delays in receiving appropriate care than White patients, showing that AI is not a “silver bullet” for eliminating inequities. AI can also perpetuate existing biases, due to limited diversity in training data, biases within the datasets themselves, and inadequate mechanisms for detecting and monitoring bias. For example, an AI model trained mostly on data from White patients to predict heart failure from electrocardiograms performed worse for Black patients, and particularly for Black women.
To use AI in cardiovascular care in a way that addresses racial and ethnic inequities, the authors stress the need for careful design, starting with meticulous data collection and a thorough review of training data. They also call for rigorous testing and continuous monitoring of algorithms to ensure they perform equally well for all groups, as well as greater diversity in the AI workforce and the involvement of stakeholders.
Learn more about this review here: https://doi.org/10.1007/s12170-024-00745-6
Reference:
Amponsah, D., Thamman, R., Brandt, E., James, C., Spector-Bagdady, K., & Yong, C.M. (2024). Artificial Intelligence to Promote Racial and Ethnic Cardiovascular Health Equity. Current Cardiovascular Risk Reports, 18(11), 153–162.