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Articles Published Processes
8/11/2026 6:12:03 AM | Browse: 5 | Download: 1
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Received |
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2026-01-06 07:54 |
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Peer-Review Started |
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2026-01-06 08:00 |
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First Decision by Editorial Office Director |
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2026-01-27 09:37 |
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Return for Revision |
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2026-01-27 09:37 |
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Revised |
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2026-01-30 15:04 |
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Publication Fee Transferred |
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2026-02-06 06:24 |
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Second Decision by Editor |
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2026-04-08 02:45 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-04-08 06:45 |
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Articles in Press |
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2026-04-08 06:45 |
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Edit the Manuscript by Language Editor |
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2026-04-13 18:40 |
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Typeset the Manuscript |
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2026-08-06 01:43 |
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Publish the Manuscript Online |
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2026-08-11 06:12 |
| ISSN |
1007-9327 (print) and 2219-2840 (online) |
| Open Access |
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| Copyright |
©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| 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 |
Artificial intelligence integrated multimodal data assisted magnetic resonance imaging for neoadjuvant chemoradiotherapy decision making in cT1-2N0 rectal cancer
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Bo-Yu Kang, He Bai, Ke Ni, Yi-Huan Qiao, Yun-Long Li, Yi-Qian Wang, Qi Wang, Jun Zhu and Ji-Peng Li |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| National Natural Science Foundation of China |
No. 82172781 |
| Shaanxi Provincial Health Scientific Research Innovation Team Project |
No. CBSKL2022ZZ44 |
| Scientific and Technological Innovation Team of Shaanxi Innovation Capability Support Plan |
No. 2023-CX-TD-67 |
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| Corresponding Author |
Ji-Peng Li, Chief Physician, Postdoc, Professor, Department of Digestive Surgery, The First Affiliated Hospital of Digestive Diseases, Air Force Medical University, No. 127 Changle West Road, Xincheng District, Xi’an 710032, Shaanxi Province, China. jipengli1974@aliyun.com |
| Key Words |
cT1-2N0 rectal cancer; Magnetic resonance imaging; Machine learning; Radiomics; SHapley Additive exPlanations; Surgery |
| Core Tip |
The artificial intelligence-driven multimodal model not only improves radiomic performance but also offers clinicians a reliable tool to reduce the regret of failing to identify patients who would have benefited from neoadjuvant therapy. Compared with radiologists’ assessments, the model also highlights its reliability and advantages in assisting clinical decision-making. |
| Publish Date |
2026-08-11 06:12 |
| Citation |
Kang BY, Bai H, Ni K, Qiao YH, Li YL, Wang YQ, Wang Q, Zhu J, Li JP. Artificial intelligence integrated multimodal data assisted magnetic resonance imaging for neoadjuvant chemoradiotherapy decision making in cT1-2N0 rectal cancer. World J Gastroenterol 2026; 32(33): 118584
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| URL |
https://www.wjgnet.com/1007-9327/full/v32/i33/118584.htm |
| DOI |
https://doi.org/10.3748/wjg.118584 |
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