Retrospective Study
Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Feb 7, 2025; 31(5): 101722
Published online Feb 7, 2025. doi: 10.3748/wjg.v31.i5.101722
Machine learning model using immune indicators to predict outcomes in early liver cancer
Yi Zhang, Ke Shi, Ying Feng, Xian-Bo Wang
Yi Zhang, Ke Shi, Ying Feng, Xian-Bo Wang, Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
Co-first authors: Yi Zhang and Ke Shi.
Author contributions: All authors contributed to the study conception and design; Feng Y performed material preparation, data collection, and analysis; Zhang Y and Shi K written the first draft of the manuscript; Wang XB reviewed and edited the manuscript; All authors commented on previous versions of the manuscript.
Supported by High-Level Chinese Medicine Key Discipline Construction Project, No. zyyzdxk-2023005; Capital Health Development Research Project, No. 2024-1-2173; and the National Natural Science Foundation of China, No. 82474426 and No. 82474419.
Institutional review board statement: The study was conducted in accordance with the Declaration of Helsinki and approved by the Beijing Ditan Hospital’s ethical committee (protocol code No. DTEC-KY2020-004-01 and date of approval: January 27, 2020).
Informed consent statement: This study was approved by the Ethics Committee of Beijing Ditan Hospital, and all patients provided written informed consent. This research was conducted in compliance with the Declaration of Helsinki, as revised in 2008.
Conflict-of-interest statement: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Data sharing statement: The data that support the findings of this study are available on request from the corresponding author at wangxb@ccmu.edu.cn.
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/
Corresponding author: Xian-Bo Wang, MD, PhD, Chief Physician, 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
Received: September 25, 2024
Revised: November 15, 2024
Accepted: December 9, 2024
Published online: February 7, 2025
Processing time: 96 Days and 8 Hours
Core Tip

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.