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Articles Published Processes
1/5/2026 3:46:24 AM | Browse: 105 | Download: 364
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Received |
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2025-07-17 02:34 |
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Peer-Review Started |
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2025-07-17 02:34 |
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First Decision by Editorial Office Director |
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2025-07-24 09:03 |
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Return for Revision |
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2025-07-24 09:03 |
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Revised |
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2025-07-30 03:33 |
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Publication Fee Transferred |
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2025-07-31 02:57 |
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Second Decision by Editor |
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2025-11-27 02:37 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2025-11-27 07:24 |
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Articles in Press |
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2025-11-27 07:24 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2025-12-25 11:25 |
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Publish the Manuscript Online |
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2026-01-05 03:46 |
| 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) 2025. 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 |
Predicting lymph node metastasis in colorectal cancer using case-level multiple instance learning
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Ling-Feng Zou, Xuan-Bing Wang, Jing-Wen Li, Xin Ouyang, Yi-Ying Luo, Yan Luo and Cheng-Long Wang |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| Chongqing Medical Scientific Research Project (Joint Project of Chongqing Health Commission and Science and Technology Bureau) |
2023MSXM060 |
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| Corresponding Author |
Cheng-Long Wang, MD, PhD, Department of Pathology, Chongqing Traditional Chinese Medicine Hospital, No. 6 Panxi 7 Branch Road, Jiangbei District, Chongqing 400021, China. qq171909771@gmail.com |
| Key Words |
Colorectal cancer; Lymph node metastasis; Deep learning; Multiple instance learning; Histopathology |
| Core Tip |
To better predict lymph node metastasis (LNM) in advanced colorectal cancer, this pilot study developed a case-level deep learning framework. By analysing the pathology slides of all patients and emulating a pathologist's workflow, the model achieved a high area under the curve of 0.899, outperforming traditional methods. Integrating the clinical data further increased the accuracy to 0.904. This interpretable approach is a promising tool for refining LNM risk assessments and guiding adjuvant therapy decisions. |
| Publish Date |
2026-01-05 03:46 |
| Citation |
Zou LF, Wang XB, Li JW, Ouyang X, Luo YY, Luo Y, Wang CL. Predicting lymph node metastasis in colorectal cancer using case-level multiple instance learning. World J Gastroenterol 2026; 32(1): 112090 |
| URL |
https://www.wjgnet.com/1007-9327/full/v32/i1/112090.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v32.i1.112090 |
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