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Articles Published Processes
6/18/2026 9:51:21 AM | Browse: 0 | Download: 0
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Received |
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2026-01-23 02:56 |
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Peer-Review Started |
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2026-01-23 02:57 |
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First Decision by Editorial Office Director |
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2026-01-28 08:40 |
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Return for Revision |
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2026-01-28 08:40 |
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Revised |
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2026-02-02 19:43 |
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Publication Fee Transferred |
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Second Decision by Editor |
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2026-02-24 02:40 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-02-24 09:30 |
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Articles in Press |
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2026-02-24 09:30 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-06-10 02:40 |
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Publish the Manuscript Online |
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2026-06-18 09:51 |
| 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: https://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. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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| Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
| Website |
http://www.wjgnet.com |
| Category |
Cardiac & Cardiovascular Systems |
| Manuscript Type |
Correspondence |
| Article Title |
Letter to the Editor: Do we need an artificial intelligence-assisted electrocardiographic tool to diagnose diabetes mellitus or to predict its unseen cardiovascular consequences?
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Ayman El-Menyar |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Ayman El-Menyar, Department of Surgery, Hamad Medical Corporation, Al-Rayyan Street, Doha 3050, Qatar. aymanco65@yahoo.com |
| Key Words |
Diabetes mellitus; Electrocardiography; Artificial intelligence-assisted; Diagnostic tool; Machine learning; Cardiovascular; Photoplethysmography; Electrocardiographic |
| Core Tip |
Diabetes mellitus (DM) has a significant negative impact on the global health. The most dramatic complications of diabetes include the microvascular damage that can start years before the diagnosis of type 2 diabetes (T2DM) is made; therefore, early screening is of utmost value. Moreover, subclinical electrocardiographic (ECG) changes are common in patients with T2DM without evident cardiac disease. A simple, easily accessible tool for early detection or prediction of cardiac dysfunction in DM or in people at risk is more valuable than merely distinguishing healthy individuals from those with diabetes or type 1 diabetes from T2DM. A single-lead ECG, especially with artificial intelligence, can red-flagging risk and help bridge some gaps in predicting event risk. However, this study needs validation with a precise aim to predict high-risk diabetics and not only to diagnose DM. |
| Publish Date |
2026-06-18 09:51 |
| Citation |
El-Menyar A. Letter to the Editor: Do we need an artificial intelligence-assisted electrocardiographic tool to diagnose diabetes mellitus or to predict its unseen cardiovascular consequences? World J Cardiol 2026; 18(6): 119266
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| URL |
https://www.wjgnet.com/1949-8462/full/v18/i6/119266.htm |
| DOI |
https://doi.org/10.4330/wjc.119266 |
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