Development and validation of machine learning models for esophagogastric variceal bleeding risk in hepatocellular carcinoma patients

doi:10.4251/wjgo.121356

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World Journal of Gastrointestinal Oncology

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1948-5204

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

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Copyright: ©Author(s) 2026. 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.

World J Gastrointest Oncol. Sep 15, 2026; 18(9): 121356
Published online Sep 15, 2026. doi: 10.4251/wjgo.121356

Table 2 Multivariate logistic regression analysis

Variable	β	SE	Waldχ²	OR	95%CI	P value
Ascites	1.371	0.610	2.246	3.939	1.190-13.031	0.025
Tumor burden score	0.283	0.111	2.555	1.327	1.068-1.648	0.011
Splenic vein diameter	0.590	0.140	4.207	1.804	1.370-2.374	< 0.01
Albumin	-0.188	0.049	-3.867	0.829	0.754-0.912	< 0.01

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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
URL: https://www.wjgnet.com/1948-5204/full/v18/i9/121356.htm
DOI: https://dx.doi.org/10.4251/wjgo.121356

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 [DOI: 10.4251/wjgo.121356]

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