Prospective evaluation of smartwatch-enabled detection of left ventricular dysfunction-Reference-Cited by-同舟云学术

Prospective evaluation of smartwatch-enabled detection of left ventricular dysfunction

Published:2022-11-14 Issue:12 Volume:28 Page:2497-2503
ISSN:1078-8956
Container-title:Nature Medicine
language:en
Short-container-title:Nat Med

Author:

Attia Zachi I.^ORCID,Harmon David M.^ORCID,Dugan Jennifer,Manka Lukas,Lopez-Jimenez Francisco,Lerman Amir^ORCID,Siontis Konstantinos C.,Noseworthy Peter A.^ORCID,Yao Xiaoxi^ORCID,Klavetter Eric W.,Halamka John D.^ORCID,Asirvatham Samuel J.^ORCID,Khan Rita,Carter Rickey E.^ORCID,Leibovich Bradley C.,Friedman Paul A.^ORCID

Publisher

Springer Science and Business Media LLC

Subject

General Biochemistry, Genetics and Molecular Biology,General Medicine

Link

https://www.nature.com/articles/s41591-022-02053-1.pdf

Reference44 articles.

1. Attia, Z. I., Harmon, D. M., Behr, E. R. & Friedman, P. A. Application of artificial intelligence to the electrocardiogram. Eur. Heart J. 42, 4717–4730 (2021).

2. Siontis, K. C., Noseworthy, P. A., Attia, Z. I. & Friedman, P. A. Artificial intelligence-enhanced electrocardiography in cardiovascular disease management. Nat. Rev. Cardiol. 18, 465–478 (2021).

3. Harmon, D. M., Attia, Z. I. & Friedman, P. A. Current and future implications of the artificial intelligence electrocardiogram: the transformation of healthcare and attendant research opportunities. Cardiovasc. Res. 118, e23–e25 (2022).

4. Attia, Z. I. et al. Screening for cardiac contractile dysfunction using an artificial intelligence-enabled electrocardiogram. Nat. Med. 25, 70–74 (2019).

5. Kwon, J. M. et al. Deep learning-based algorithm for detecting aortic stenosis using electrocardiography. J. Am. Heart Assoc. 9, e014717 (2020).

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