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Articles Published Processes
4/25/2021 8:01:44 AM | Browse: 506 | Download: 1102
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Received |
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2021-01-27 15:06 |
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Peer-Review Started |
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2021-01-27 15:08 |
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To Make the First Decision |
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Return for Revision |
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2021-03-07 12:30 |
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Revised |
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2021-03-21 05:08 |
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Second Decision |
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2021-04-19 06:24 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2021-04-20 05:10 |
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Articles in Press |
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2021-04-20 05:10 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2021-04-25 01:38 |
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Publish the Manuscript Online |
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2021-04-25 08:01 |
ISSN |
2644-3236 (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 |
© The Author(s) 2021. 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 |
Review |
Article Title |
Artificial intelligence in gastrointestinal radiology: A review with special focus on recent development of magnetic resonance and computed tomography
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Manuscript Source |
Invited Manuscript |
All Author List |
Kai-Po Chang, Shih-Huan Lin and Yen-Wei Chu |
ORCID |
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Funding Agency and Grant Number |
Funding Agency |
Grant Number |
Ministry of Science and Technology |
109-2321-B-005-024 |
Ministry of Science and Technology |
109-2320-B-039-005 |
National Chung Hsing University and Chung-Shan Medical University |
NCHU-CSMU 10911 |
China Medical University Hospital |
DMR-109-258 |
ChangHua Christian Hospital and National Chung Hsing University |
NCHU-CCH-11006 |
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Corresponding Author |
Yen-Wei Chu, PhD, Director, Director, Professor, Institute of Genomics and Bioinformatics, National Chung Hsing University, Kuo Kuang Rd., Taichung 40227, Taiwan. ywchu@nchu.edu.tw |
Key Words |
Artificial intelligence; Deep learning; Image diagnosis; Radiology; Magnetic resonance imaging; Computed tomography |
Core Tip |
Gastrointestinal radiology is a subspecialty that is important and complex, and is thus a popular subject in artificial intelligence (AI). Recently many deep-learning based diagnosis assistance tool have been developed in gastrointestinal radiology, particularly in diagnostic abdominal magnetic resonance imaging (MRI) and computed tomography (CT). Herein we will review recent advance of AI in gastrointestinal radiology, with a special focus on abdominal MRI and CT. Current difficulty in less-developed fields will be explained as well. |
Publish Date |
2021-04-25 08:01 |
Citation |
Chang KP, Lin SH, Chu YW. Artificial intelligence in gastrointestinal radiology: A review with special focus on recent development of magnetic resonance and computed tomography. Artif Intell Gastroenterol 2021; 2(2): 37-41 |
URL |
https://www.wjgnet.com/2644-3236/full/v2/i2/27.htm |
DOI |
https://dx.doi.org/10.35712/aig.v2.i2.27 |
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