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Articles Published Processes
6/10/2022 5:40:20 AM | Browse: 280 | Download: 608
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Received |
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2021-04-27 13:09 |
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Peer-Review Started |
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2021-04-28 12:20 |
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To Make the First Decision |
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Return for Revision |
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2021-06-13 03:40 |
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Revised |
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2021-07-27 05:24 |
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Second Decision |
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2022-04-28 03:28 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Company Editor-in-Chief |
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2022-04-28 20:47 |
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Articles in Press |
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2022-04-28 20:47 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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2022-04-18 09:03 |
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Typeset the Manuscript |
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2022-05-26 08:23 |
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Publish the Manuscript Online |
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2022-06-10 05:40 |
| 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: http://creativecommons.org/Licenses/by-nc/4.0/ |
| Copyright |
©The Author(s) 2022. 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 |
Application of endoscopic ultrasonography for detecting esophageal lesions based on convolutional neural network
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Gao-Shuang Liu, Pei-Yun Huang, Min-Li Wen, Shuai-Shuai Zhuang, Jie Hua and Xiao-Pu He |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| the Natural Science Foundation of Jiangsu |
BK20171508 |
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| Corresponding Author |
Jie Hua, MD, Chief Physician, Doctor, Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, No. 300 Guangzhou Road, Nanjing 210000, Jiangsu Province, China. huajie@njmu.edu.cn |
| Key Words |
Endoscopic ultrasonography; Convolutional neural network; Esophageal lesion; Automatically; Classify; Identify |
| Core Tip |
Convolutional neural networks with self-learning abilities are an effective method in medical image classification, segmentation, and detection. Endoscopic ultrasonography plays an important role in the diagnosis and treatment of esophageal lesions. However, its operation and lesion identification are more difficult than ordinary endoscopy. Automatic identification technology is of great significance to its development. |
| Publish Date |
2022-06-10 05:40 |
| Citation |
Liu GS, Huang PY, Wen ML, Zhuang SS, Hua J, He XP. Application of endoscopic ultrasonography for detecting esophageal lesions based on convolutional neural network. World J Gastroenterol 2022; 28(22): 2457-2467 |
| URL |
https://www.wjgnet.com/1007-9327/full/v28/i22/2457.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v28.i22.2457 |
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