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Articles Published Processes
9/9/2026 9:45:13 AM | Browse: 3 | Download: 0
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Received |
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2026-03-23 03:46 |
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Peer-Review Started |
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2026-03-23 03:46 |
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First Decision by Editorial Office Director |
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2026-04-15 08:20 |
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Return for Revision |
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2026-04-15 09:13 |
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Revised |
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2026-05-06 17:23 |
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Publication Fee Transferred |
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2026-05-13 07:19 |
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Second Decision by Editor |
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2026-06-18 02:31 |
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Second Decision by Editor-in-Chief |
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Final Decision by Editorial Office Director |
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2026-06-18 07:14 |
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Articles in Press |
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2026-06-18 07:14 |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2026-08-24 00:33 |
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Publish the Manuscript Online |
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2026-09-09 09:45 |
| ISSN |
1948-5204 (online) |
| Open Access |
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| Copyright |
©Author(s) (or their employer(s)) 2026. No commercial re-use. See Permissions. Published by Baishideng Publishing Group Inc. |
| 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 |
Retrospective Study |
| Article Title |
Development and validation of machine learning models for esophagogastric variceal bleeding risk in hepatocellular carcinoma patients
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| Manuscript Source |
Unsolicited Manuscript |
| All Author List |
Qiao Luo, Chao Zhang and Yong-Ping Luo |
| ORCID |
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| Funding Agency and Grant Number |
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| Corresponding Author |
Yong-Ping Luo, Department of Gastroenterology, Yibin Second People's Hospital, No. 96, Beida Street, Cuiping District, Yibin 644000, Sichuan Province, China. lyp365e@163.com |
| Key Words |
Hepatocellular carcinoma; Esophagogastric variceal bleeding; Machine learning; Prediction model; SHapley Additive exPlanation |
| Core Tip |
This study developed and validated six machine learning models for the early identification of the risk of early-stage esophagogastric variceal bleeding in patients with hepatocellular carcinoma. Albumin, splenic vein diameter, tumor burden score, and ascites were identified as feature variables through LASSO and multivariate Logistic regression. Based on these variables, six machine learning models were constructed, and the support vector machine model was selected as the optimal model. This model demonstrated satisfactory predictive performance, calibration, and clinical applicability. |
| Publish Date |
2026-09-09 09:45 |
| Citation |
Luo Q, Zhang C, Luo YP. Development and validation of machine learning models for esophagogastric variceal bleeding risk in hepatocellular carcinoma patients. World J Gastrointest Oncol 2026; 18(9): 121356
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| URL |
https://www.wjgnet.com/1948-5204/full/v18/i9/121356.htm |
| DOI |
https://doi.org/10.4251/wjgo.121356 |
Copyright © 1993-2026 Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA. All rights reserved, including rights relating to text and data mining, AI training, and similar technologies. For open-access content, the applicable copyright and licensing terms govern.
