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Articles Published Processes
2/21/2024 9:11:33 AM | Browse: 78 | Download: 111
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Received |
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2023-11-13 03:52 |
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Peer-Review Started |
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2023-11-13 03:54 |
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To Make the First Decision |
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Return for Revision |
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2023-12-05 23:57 |
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Revised |
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2023-12-12 03:27 |
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Second Decision |
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2024-01-22 02:39 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Company Editor-in-Chief |
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2024-01-22 04:25 |
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Articles in Press |
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2024-01-22 04:25 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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2024-01-21 22:36 |
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Typeset the Manuscript |
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2024-02-05 03:00 |
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Publish the Manuscript Online |
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2024-02-21 09:11 |
| 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) 2024. 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 |
Editorial |
| Article Title |
From prediction to prevention: Machine learning revolutionizes hepatocellular carcinoma recurrence monitoring
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Mariana Michelle 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, FAASLD, AGAF, FACG, MD, MSc, PhD, Doctor, Professor, Liver Research Unit, Medica Sur Clinic & Foundation, Puente de Piedra 150, Col. Toriello Guerra, Distrito Federal 14050, Mexico. nah@unam.mx |
| Key Words |
Hepatocellular carcinoma; Early recurrence; Machine learning; XGBoost model; Predictive precision medicine; Clinical utility; Personalized interventions |
| Core Tip |
Machine learning is an important approach for personalized oncology care, as it paves the way for precise and individualized postoperative strategies, thereby enhancing patient outcomes in the field of hepatocellular carcinoma treatment. Ongoing collaboration, larger sample sizes, and multicenter studies are crucial for validating and refining this innovative predictive model, thus ensuring its applicability and reliability in diverse clinical settings. |
| Publish Date |
2024-02-21 09:11 |
| Citation |
Ramírez-Mejía MM, Méndez-Sánchez N. From prediction to prevention: Machine learning revolutionizes hepatocellular carcinoma recurrence monitoring. World J Gastroenterol 2024; 30(7): 631-635 |
| URL |
https://www.wjgnet.com/1007-9327/full/v30/i7/631.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v30.i7.631 |
© 2004-2024 Baishideng Publishing Group Inc. All rights reserved. 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
California Corporate Number: 3537345
