Summary
AHA’s first scientific statement on AI in cardiovascular care outlines priorities for data quality (representativeness, provenance), transparency and validation, clinical trial design and reporting for AI tools, workflow integration, and post‑deployment monitoring. It calls for multidisciplinary governance, rigorous external validation, and bias assessment across the Computer Vision care continuum (imaging, risk prediction, triage, and therapeutics).
Healthcare Implications
Cardiology programs using AI (e.g., Computer Vision imaging triage, risk models) can map local governance and study designs to the statement: require dataset documentation, bias audits, prospective evaluation before scale‑up, and ongoing performance surveillance with human oversight and clear accountability.