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AI Echo in Cardiovascular Disease Management
- james142268
- Nov 18, 2025
- 2 min read
Article | Aug 6, 2025
Artificial intelligence (AI) is reshaping the field of echocardiography, paving the way for greater diagnostic accuracy, improved workflow efficiency, and enhanced patient care. In this newly published review article, the authors provide a comprehensive examination of how AI is being applied across the echocardiographic workflow, from image acquisition and analysis to interpretation.
The review highlights recent technological advancements, practical clinical implementations, and future opportunities for AI integration. It explores how AI can automate routine measurements, support task shifting, identify disease-specific patterns, and reveal novel phenogroups that may go beyond traditional diagnostic classifications.
Crucially, the article also discusses the essential components required to build trustworthy AI systems, including rigorous validation, regulatory compliance, and adherence to ethical standards. By presenting both the promises and limitations of current AI technologies, the review offers a balanced and insightful perspective on the role of AI in the evolving landscape of cardiovascular imaging.
Through analysis of emerging tools, clinical studies, and real-world applications, this work highlights AI’s potential to transform echocardiography and advance cardiovascular care on a global scale.
Application of AI along the echocardiography workflow
Potential clinical applications of Al-assisted echocardiography
Guiding principles for trustworthy Al in echocardiography
Real-world implementation of Al-assisted echocardiography
A roadmap for the integration of Al-assisted echocardiography into clinical practice
Myhre, P. L., Grenne, B., Asch, F. M., Delgado, V., Khera, R., Lafitte, S., Lang, R. M., Pellikka, P. A., Sengupta, P. P., Vemulapalli, S., & Lam, C. S. P (2025). Artificial intelligence-enhanced echocardiography in cardiovascular disease management. Nature Reviews Cardiology, 1–19. https://doi.org/10.1038/s41569-025-01197-0
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