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Citation of this article
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 [PMID: 38515945 DOI: 10.3748/wjg.v30.i7.631]

Corresponding Author of This Article
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

Research Domain of This Article
Gastroenterology & Hepatology

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Editorial

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This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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/

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Feb 21, 2024 (publication date) through Oct 22, 2025
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Journal Information of This Article
Publication Name
World Journal of Gastroenterology
ISSN
1007-9327
Publisher of This Article
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
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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 [PMID: 38515945 DOI: 10.3748/wjg.v30.i7.631] | |
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For: | 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 [PMID: 38515945 DOI: 10.3748/wjg.v30.i7.631] |
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URL: | https://www.wjgnet.com/1948-5182/full/v30/i7/631.htm |
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