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Recent AI advancements in cardiovascular care offer potential enhancements in diagnosis, treatment, and outcomes. Innovations to date focus on automating measurements, enhancing image quality, and detecting diseases using novel methods. Applications span wearables, electrocardiograms, echocardiography, angiography, genetics, and more. AI models detect diseases from electrocardiograms at accuracy not previously achieved by technology or human experts, including reduced ejection fraction, valvular heart disease, and other cardiomyopathies. However, AI's unique characteristics necessitates rigorous validation by addressing training methods, real-world efficacy, equity concerns, and long-term reliability. Despite an exponentially growing number of studies in cardiovascular AI, trials showing improvement in outcomes remain lacking. A number are currently underway. Embracing this rapidly evolving technology while setting a high evaluation benchmark will be crucial for cardiology to leverage AI to enhance patient care and the provider experience.
“AI technologies have shown early promise in screening for disease, integrating disparate imaging data sources into composite assessments, providing workflow efficiencies through preprocessing of images, and assisting clinicians with more accurate diagnoses.”
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Pierre Elias
Sneha S. Jain
Timothy J. Poterucha
Journal of the American College of Cardiology
Stanford University
Cornell University
Yale University
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Elias et al. (Sun,) studied this question.
www.synapsesocial.com/papers/69fc04a3ee94d1bf1bb2f768 — DOI: https://doi.org/10.1016/j.jacc.2024.03.400