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Articles Published Processes
6/6/2025 3:09:38 AM | Browse: 10 | Download: 45
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Received |
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2025-03-09 09:45 |
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Peer-Review Started |
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2025-03-09 09:45 |
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To Make the First Decision |
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Return for Revision |
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2025-03-26 21:06 |
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Revised |
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2025-04-15 19:40 |
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Second Decision |
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2025-05-12 02:38 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2025-05-12 05:13 |
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Articles in Press |
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2025-05-12 05:13 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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2025-05-17 23:12 |
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Typeset the Manuscript |
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2025-05-30 09:25 |
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Publish the Manuscript Online |
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2025-06-06 03:09 |
| 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) 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 |
Letter to the Editor |
| Article Title |
Outcome prediction for cholangiocarcinoma prognosis: Embracing the machine learning era
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Arnulfo E Morales-Galicia, Mariana N Rincón-Sánchez, Mariana M Ramírez-Mejía and Nahum Méndez-Sánchez |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Nahum Méndez-Sánchez, Liver Research Unit, Medica Sur Clinic and Foundation, Puente de Piedra 150, Col. Toriello Guerra, Mexico City 14050, Mexico. nah@unam.mx |
| Key Words |
Cholangiocarcinoma; Artificial intelligence; Liver tumor; Prognosis; Survival |
| Core Tip |
Machine learning-driven preoperative risk stratification enhances surgical planning in intrahepatic cholangiocarcinoma. Huang et al demonstrated that the concept of the textbook outcome can be predicted preoperatively using artificial intelligence models, which outperform traditional prognostic methods. Their study underscores the importance of dynamic, data-driven approaches for improving disease-free survival and optimizing patient selection for curative resection. |
| Publish Date |
2025-06-06 03:09 |
| Citation |
<p>Morales-Galicia AE, Rincón-Sánchez MN, Ramírez-Mejía MM, Méndez-Sánchez N. Outcome prediction for cholangiocarcinoma prognosis: Embracing the machine learning era. <i>World J Gastroenterol</i> 2025; 31(21): 106808</p> |
| URL |
https://www.wjgnet.com/1007-9327/full/v31/i21/106808.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v31.i21.106808 |
© 2004-2025 Baishideng Publishing Group Inc. All rights reserved. 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
California Corporate Number: 3537345
