Publication Name	World Journal of Gastroenterology
Manuscript ID	101722
Country	China

Received	2024-09-25 01:52
Peer-Review Started	2024-09-25 01:52
To Make the First Decision
Return for Revision	2024-11-09 19:30
Revised	2024-11-15 08:12
Second Decision	2024-12-09 02:36
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2024-12-09 06:44
Articles in Press	2024-12-09 06:44
Publication Fee Transferred	2024-11-18 11:19
Edit the Manuscript by Language Editor
Typeset the Manuscript	2024-12-20 06:36
Publish the Manuscript Online	2024-12-30 09:49

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
Permissions	For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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	Machine learning model using immune indicators to predict outcomes in early liver cancer
Manuscript Source	Unsolicited Manuscript
All Author List	Yi Zhang, Ke Shi, Ying Feng and Xian-Bo Wang
ORCID	Author(s) ORCID Number Yi Zhang http://orcid.org/0000-0002-6515-740X Ke Shi http://orcid.org/0000-0002-3522-4667 Xian-Bo Wang http://orcid.org/0000-0002-3593-5741
Funding Agency and Grant Number	Funding Agency Grant Number High-Level Chinese Medicine Key Discipline Construction Project zyyzdxk-2023005 Capital Health Development Research Project 2024-1-2173 National Natural Science Foundation of China 82474426 and 82474419
Corresponding Author	Xian-Bo Wang, Chief Physician, MD, PhD, Professor, Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, No. 8 Jing Shun East Street, Chaoyang District, Beijing 100015, China. wangxb@ccmu.edu.cn
Key Words	Hepatocellular carcinoma; Inflammation; Machine learning; Prognosis; Artificial neural networks; Immune biomarkers
Core Tip	This study developed a predictive model using machine learning algorithms that integrates immune-inflammatory biomarkers to forecast the long-term prognosis of patients following surgical resection for early-stage hepatocellular carcinoma. This model aims to optimize screening and treatment strategies.
Publish Date	2024-12-30 09:49
Citation	<p>Zhang Y, Shi K, Feng Y, Wang XB. Machine learning model using immune indicators to predict outcomes in early liver cancer. <i>World J Gastroenterol</i> 2025; 31(5): 101722</p>
URL	https://www.wjgnet.com/1007-9327/full/v31/i5/101722.htm
DOI	https://dx.doi.org/10.3748/wjg.v31.i5.101722

Full Article (PDF)	WJG-31-101722-with-cover.pdf
Manuscript File	101722_Auto_Edited_082627.docx
Answering Reviewers	101722-answering-reviewers.pdf
Audio Core Tip	101722-audio.mp3
Biostatistics Review Certificate	101722-biostatistics-statement.pdf
Conflict-of-Interest Disclosure Form	101722-conflict-of-interest-statement.pdf
Copyright License Agreement	101722-copyright-assignment.pdf
Approved Grant Application Form(s) or Funding Agency Copy of any Approval Document(s)	101722-foundation-statement.pdf
Signed Informed Consent Form(s) or Document(s)	101722-informed-consent-statement.pdf
Institutional Review Board Approval Form or Document	101722-institutional-review-board-statement.pdf
Non-Native Speakers of English Editing Certificate	101722-non-native-speakers.pdf
Supplementary Material	101722-supplementary-material.pdf
Peer-review Report	101722-peer-reviews.pdf
Scientific Misconduct Check	101722-scientific-misconduct-check.png
Scientific Editor Work List	101722-scientific-editor-work-list.pdf
CrossCheck Report	101722-crosscheck-report.pdf