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Articles Published Processes
6/20/2025 9:55:25 AM | Browse: 21 | Download: 86
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Received |
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2025-01-22 10:18 |
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Peer-Review Started |
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2025-01-22 10:18 |
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To Make the First Decision |
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Return for Revision |
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2025-04-20 04:06 |
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Revised |
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2025-05-03 07:32 |
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Second Decision |
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2025-06-05 02:41 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2025-06-05 07:24 |
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Articles in Press |
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2025-06-05 07:24 |
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Publication Fee Transferred |
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2025-05-07 05:13 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2025-06-16 02:42 |
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Publish the Manuscript Online |
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2025-06-20 09:55 |
ISSN |
1007-9327 (print) and 2219-2840 (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 |
© The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved. |
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 |
Gastroenterology & Hepatology |
Manuscript Type |
Minireviews |
Article Title |
Recent advances in machine learning for precision diagnosis and treatment of esophageal disorders
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Manuscript Source |
Unsolicited Manuscript |
All Author List |
Shao-Wen Liu, Peng Li, Xiao-Qing Li, Qi Wang, Jin-Yu Duan, Jin Chen, Ru-Hong Li and Yang-Fan Guo |
ORCID |
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Funding Agency and Grant Number |
Funding Agency |
Grant Number |
Central Funds Guiding the Local Science and Technology Development |
No. 202207AB110017 |
Key Research and Development Program of Yunnan |
No. 202302AD080004 |
Yunnan Academician and Expert Workstation |
No. 202205AF150023 |
Scientific and Technological Innovation Team in Kunming Medical University |
No. CXTD202215 |
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Corresponding Author |
Yang-Fan Guo, Associate Professor, Precision Medicine Center, Yan’an Hospital Affiliated to Kunming Medical University, No. 245 East Renmin Road, Kunming 650051, Yunnan Province, China. guoyangfan@kmmu.edu.cn |
Key Words |
Esophageal disorders; Machine learning; Gastroesophageal reflux disease; Esophageal cancer; Barrett’s esophagus; Achalasia; Clinical decision support system |
Core Tip |
This review synthesizes machine learning (ML) applications in esophageal disorders, emphasizing three critical advances: (1) Automated analysis of multimodal diagnostic data achieving accuracy rates of 80%-95% across different conditions; (2) Integration of deep learning with endoscopic imaging enabling real-time assistance in diagnosis and risk stratification; and (3) Development of novel non-invasive screening approaches through ML-based biomarker identification. The convergence of artificial intelligence with clinical medicine demonstrates transformative potential in addressing current diagnostic challenges and enabling precision medicine in esophageal disease management. |
Publish Date |
2025-06-20 09:55 |
Citation |
<p>Liu SW, Li P, Li XQ, Wang Q, Duan JY, Chen J, Li RH, Guo YF. Recent advances in machine learning for precision diagnosis and treatment of esophageal disorders. <i>World J Gastroenterol</i> 2025; 31(23): 105076</p> |
URL |
https://www.wjgnet.com/1007-9327/full/v31/i23/105076.htm |
DOI |
https://dx.doi.org/10.3748/wjg.v31.i23.105076 |
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