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Articles Published Processes
1/12/2024 8:02:47 AM | Browse: 233 | Download: 676
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Received |
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2023-11-08 04:22 |
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Peer-Review Started |
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2023-11-08 04:24 |
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To Make the First Decision |
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Return for Revision |
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2023-12-07 06:05 |
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Revised |
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2023-12-15 05:16 |
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Second Decision |
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2023-12-19 03:36 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2023-12-26 05:57 |
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Articles in Press |
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2023-12-26 05:57 |
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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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2024-01-08 06:19 |
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Publish the Manuscript Online |
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2024-01-12 08:02 |
| 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) 2023. 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 |
Retrospective Study |
| Article Title |
Automatic detection of small bowel lesions with different bleeding risks based on deep learning models
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Rui-Ya Zhang, Peng-Peng Qiang, Ling-Jun Cai, Tao Li, Yan Qin, Yu Zhang, Yi-Qing Zhao and Jun-Ping Wang |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| The Shanxi Provincial Administration of Traditional Chinese Medicine |
2023ZYYDA2005 |
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| Corresponding Author |
Jun-Ping Wang, MD, PhD, Chief Physician, Professor, Department of Gastroenterology, The Fifth Clinical Medical College of Shanxi Medical University, No. 29 Shuangtasi Street, Taiyuan 030012, Shanxi Province, China. wangjp8396@sxmu.edu.cn |
| Key Words |
Artificial intelligence; Deep learning; Capsule endoscopy; Image classification; Object detection; Bleeding risk |
| Core Tip |
In clinical practice, capsule endoscopy is often used to detect small bowel (SB) lesions and find the cause of bleeding. Here, we have proposed a classification and detection model to automatically identify various SB lesions and their bleeding risks, and label the lesions accurately. This model can enhance the diagnostic efficiency of physicians and improve the ability of physicians to identify high-risk bleeding groups. |
| Publish Date |
2024-01-12 08:02 |
| Citation |
Zhang RY, Qiang PP, Cai LJ, Li T, Qin Y, Zhang Y, Zhao YQ, Wang JP. Automatic detection of small bowel lesions with different bleeding risks based on deep learning models. World J Gastroenterol 2023; 30(2): 170-183 |
| URL |
https://www.wjgnet.com/1007-9327/full/v30/i2/170.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v30.i2.170 |
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