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Publication Name World Journal of Cardiology
Manuscript ID 119678
DOI 10.4330/wjc.119678
Country China
Category Cardiac & Cardiovascular Systems
Manuscript Type Opinion Review
Article Title Advances in the application of artificial intelligence-enhanced electrocardiogram to non-cardiovascular diseases
Manuscript Source Invited Manuscript
All Author List Wen-Hua Song, Xing-Liang Wu, Gary Tse and Tong Liu
Funding Agency and Grant Number
Funding Agency Grant Number
Tianjin Key Medical Discipline Construction Project TJYXZDXK-3-006B
Corresponding Author Tong Liu, PhD, Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, The Second Hospital of Tianjin Medical University, No. 23 Pingjiang Road, Hexi District, Tianjin 300211, China. liutongdoc@126.com
Key Words Artificial intelligence; Machine learning; Electrocardiogram; Application; Non-cardiovascular diseases
Core Tip This article systematically reviews the latest advances in artificial intelligence-enhanced electrocardiogram for the diagnosis and evaluation of non-cardiovascular diseases. It summarizes its value in identifying and predicting risks across various conditions, including liver and kidney diseases, pulmonary embolism, and electrolyte disturbances. The opinion review also discusses the strengths, limitations, and future directions of this technology, aiming to inform clinicians and support clinical decision-making.
Citation Song WH, Wu XL, Tse G, Liu T. Advances in the application of artificial intelligence-enhanced electrocardiogram to non-cardiovascular diseases. World J Cardiol 2026; In press
PDF 119678-in-press.pdf
Received
2026-02-05 01:03
Peer-Review Started
2026-02-05 01:05
First Decision by Editorial Office Director
2026-03-13 09:22
Return for Revision
2026-03-13 09:22
Revised
2026-03-17 14:07
Publication Fee Transferred
Second Decision by Editor
2026-06-10 02:33
Second Decision by Editor-in-Chief
Final Decision by Editorial Office Director
2026-06-10 07:57
Articles in Press
2026-06-10 07:57
Edit the Manuscript by Language Editor
Typeset the Manuscript
ISSN 1949-8462 (online)
Open Access This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Copyright ©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc.
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