(Press-News.org) About The Study: Across multinational cohorts, a noise-adapted artificial intelligence (AI)-electrocardiogram (ECG) model estimated heart failure risk using lead I ECGs, suggesting a potential heart failure risk-stratification strategy requiring prospective study using wearable and portable ECG devices.
Corresponding Author: To contact the corresponding author, Rohan Khera, MD, MS, email rohan.khera@yale.edu.
To access the embargoed study: Visit our For The Media website at this link https://media.jamanetwork.com/
(doi:10.1001/jamacardio.2025.0492)
Editor’s Note: Please see the article for additional information, including other authors, author contributions and affiliations, conflicts of interest and financial disclosures, and funding and support.
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Embed this link to provide your readers free access to the full-text article This link will be live at the embargo time https://jamanetwork.com/journals/jamacardiology/fullarticle/10.1001/jamacardio.2025.0492?guestAccessKey=aadc3c8c-03cf-4e4b-9b5a-4e521211870b&utm_source=for_the_media&utm_medium=referral&utm_campaign=ftm_links&utm_content=tfl&utm_term=041625
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AI–enabled prediction of heart failure risk from single-lead electrocardiograms
JAMA Cardiology
2025-04-16
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[Press-News.org] AI–enabled prediction of heart failure risk from single-lead electrocardiogramsJAMA Cardiology