Duishanbai A, Yu YB. Application of artificial intelligence model in precise risk stratification and treatment decision-making for acute variceal bleeding in cirrhosis. World J Gastroenterol 2026; 32(30): 115546 [DOI: 10.3748/wjg.115546]
Corresponding Author of This Article
Yan-Bo Yu, Chief Physician, Professor, Department of Gastroenterology, Qilu Hospital of Shandong University, No. 107 Wenhuaxi Road, Jinan 250012, Shandong Province, China. yuyanbo2000@126.com
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Duishanbai A, Yu YB. Application of artificial intelligence model in precise risk stratification and treatment decision-making for acute variceal bleeding in cirrhosis. World J Gastroenterol 2026; 32(30): 115546 [DOI: 10.3748/wjg.115546]
World J Gastroenterol. Aug 14, 2026; 32(30): 115546 Published online Aug 14, 2026. doi: 10.3748/wjg.115546
Application of artificial intelligence model in precise risk stratification and treatment decision-making for acute variceal bleeding in cirrhosis
Ahemala Duishanbai, Yan-Bo Yu
Ahemala Duishanbai, Yan-Bo Yu, Department of Gastroenterology, Qilu Hospital of Shandong University, Jinan 250012, Shandong Province, China
Author contributions: Duishanbai A performed the bibliographic search; Duishanbai A and Yu YB designed the overall concept and outline of the manuscript; Yu YB revised the article critically for important intellectual content; all authors approved the final version of the manuscript.
Supported by National Natural Science Foundation of China, No. 82070540; Taishan Scholars Program of Shandong Province, No. tsqn202211309; National Key Research and Development Program, No. 2022YFC2504000; Natural Science Foundation of Shandong Province, No. ZR2024 LSW013; and Scientific Research Project of Shandong Medical Association, No. YXH2024YS027.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Corresponding author: Yan-Bo Yu, Chief Physician, Professor, Department of Gastroenterology, Qilu Hospital of Shandong University, No. 107 Wenhuaxi Road, Jinan 250012, Shandong Province, China. yuyanbo2000@126.com
Received: October 20, 2025 Revised: December 18, 2025 Accepted: February 2, 2026 Published online: August 14, 2026 Processing time: 276 Days and 21.1 Hours
Abstract
This editorial focuses on a recent study by Xiang et al published on the World Journal of Gastroenterology that developed and validated an artificial intelligence-driven model to refine risk stratification and guide personalized treatment plans for acute variceal bleeding (AVB) in cirrhotic patients. The predictive model was constructed using clinical data collected within the first 24 hours following patient admission. Its superior predictive accuracy translates into a critical clinical application: The model effectively identifies high-risk patients who would derive the greatest benefit from preemptive transjugular intrahepatic portosystemic shunt, and simultaneously identifies low-risk patients for whom such an invasive procedure can be safely avoided. The artificial intelligence-AVB model represents a practical application of precision medicine by translating complex data into actionable, personalized strategies for the treatment of AVB.
Core Tip: This editorial reviews the non-invasive diagnostic techniques for portal hypertension and the application progress of artificial intelligence in the screening, diagnosis, and treatment of cirrhosis-related gastroesophageal varices. It focuses on exploring the application value of artificial intelligence in the risk stratification assessment of high-risk gastroesophageal variceal bleeding, post-bleeding condition monitoring, and the formulation of individualized diagnosis and treatment decisions.
