| For: | Peng YJ, Liu X, Liu Y, Tang X, Zhao QP, Du Y. Computed tomography-based multi-organ radiomics nomogram model for predicting the risk of esophagogastric variceal bleeding in cirrhosis. World J Gastroenterol 2024; 30(36): 4044-4056 [PMID: 39351251 DOI: 10.3748/wjg.v30.i36.4044] |
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| URL: | https://www.wjgnet.com/1007-9327/full/v30/i36/4044.htm |
| Number | Citing Articles |
| 1 |
Sahib Singh, Saurabh Chandan, Rakesh Vinayek, Ganesh Aswath, Antonio Facciorusso, Marcello Maida. Comprehensive approach to esophageal variceal bleeding: From prevention to treatment. World Journal of Gastroenterology 2024; 30(43): 4602-4608 doi: 10.3748/wjg.v30.i43.4602
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| 2 |
Minh Huu Nhat Le, Hien Quang Kha, Nghia Minh Tran, Phat Ky Nguyen, Han H. Huynh, Phat Kim Huynh, Han Lam, Nguyen Quoc Khanh Le. Radiomics in liver research: A paradigm shift in disease detection and staging. European Journal of Radiology Artificial Intelligence 2025; 2 doi: 10.1016/j.ejrai.2025.100016
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| 3 |
Yi Kiat Isaac Kuan, Yixin Jamie Kok, Nigel Sheng Hui Liu, Brandon Jin An Ong, Ying Jie Chee, Chuanhui Xu, Minyang Chow, Kollengode Ramanathan, Rinkoo Dalan, Prahlad Ho, Bingwen Eugene Fan. Artificial intelligence in clinical thrombosis and hemostasis: A review. Research and Practice in Thrombosis and Haemostasis 2025; 9(5) doi: 10.1016/j.rpth.2025.102984
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| 4 |
Naoshi Nishida. Advancements in Artificial Intelligence-Enhanced Imaging Diagnostics for the Management of Liver Disease—Applications and Challenges in Personalized Care. Bioengineering 2024; 11(12) doi: 10.3390/bioengineering11121243
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| 5 |
Jin Peng, Huiru Jin, Ningxin Zhang, Shiqiu Zheng, Chengxiao Yu, Jianzhong Yu, Longfeng Jiang. Development and evaluation of a predictive model of upper gastrointestinal bleeding in liver cirrhosis. BMC Gastroenterology 2025; 25(1) doi: 10.1186/s12876-025-03677-6
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| 6 |
Chao Zhu, Qi Liu, Wenhui Tao, Bolun Fu, Fengyong Yang, Kun Yang, Yuzhen Bao, Bin Cao, Lili Liu, Jiafu Ma, Fan Qi, Shuai Han, Xin Lian. Predictive performance of CT-based artificial intelligence for predicting variceal bleeding in portal hypertension: a systematic review and meta-analysis. Abdominal Radiology 2026; doi: 10.1007/s00261-026-05564-4
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| 7 |
Yong Chen, Yueyu Shen, Xiaohan Wang. Artificial Intelligence in Managing Liver Cirrhosis and Variceal Bleeding: A Review. Hepatitis Monthly 2025; 25(1) doi: 10.5812/hepatmon-160500
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| 8 |
Hong Liu, Yingxia She, Junlin Zhou. Predicting the Grade of Esophageal Varices in Cirrhosis Based on Spectral Computed Tomography Radiomics. Indian Journal of Radiology and Imaging 2026; doi: 10.1055/s-0046-1815932
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| 9 |
Qiuhui Tian, Yu Liu, Qiumei Cao, Mingjing Cheng, Meixu Zhang, Fengying Zhu, Yukai He. Clinical Value of APRI and FIB-4 on Bleeding Risk and 30-Day Prognosis in Patients with Liver Cirrhosis Complicated with Esophagogastric Varices. International Journal of General Medicine 2025; doi: 10.2147/IJGM.S545850
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| 10 |
Zuo-Jun Li, Jing Chen, Li Li, Yu-Tao Zhan. Development of a nomogram model based on spleen volume change to predict high-risk esophageal varices in patients with liver cirrhosis. Frontiers in Surgery 2026; 12 doi: 10.3389/fsurg.2025.1699002
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| 11 |
Carlos Moctezuma-Velazquez, Juan G. Abraldes. Future of Endoscopy in Surveillance of Esophageal Varices. Current Gastroenterology Reports 2025; 27(1) doi: 10.1007/s11894-025-00976-6
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| 12 |
Arunkumar Krishnan. Improving radiomics-based models for esophagogastric variceal bleeding risk prediction in cirrhotic patients. World Journal of Gastroenterology 2025; 31(11): 101804 doi: 10.3748/wjg.v31.i11.101804
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| 13 |
Henrique Coelho, Fernando Silva, Marta Correia, Pedro Miguel Rodrigues. Artificial Intelligence in Patient Blood Management: A Systematic Review of Predictive, Diagnostic, and Decision Support Applications. Journal of Clinical Medicine 2025; 14(23) doi: 10.3390/jcm14238479
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| 14 |
文卿 屈. Research Progress of SII/SIRI in Predicting Esophageal and Gastric Variceal Bleeding in Liver Cirrhosis. Advances in Clinical Medicine 2026; 16(07) doi: 10.12677/acm.2026.1672559
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