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Cited by in CrossRef
For: Luo R, Gao J, Gan W, Xie WB. Clinical-radiomics nomogram for predicting esophagogastric variceal bleeding risk noninvasively in patients with cirrhosis. World J Gastroenterol 2023; 29(6): 1076-1089 [PMID: 36844133 DOI: 10.3748/wjg.v29.i6.1076]
URL: https://www.wjgnet.com/1007-9327/full/v29/i6/1076.htm
Number Citing Articles
1
Cheng Yan, Min Li, Changchun Liu, Zhe Zhang, Jingwen Zhang, Mingzi Gao, Jing Han, Mingxin Zhang, Liqin Zhao. Development of a non-invasive diagnostic model for high-risk esophageal varices based on radiomics of spleen CTAbdominal Radiology 2024; 49(12): 4373 doi: 10.1007/s00261-024-04509-z
2
Camila Guinazu, Adolfo Fernández Muñoz, Maria D Maldonado, Jeffry A De La Cruz, Domenica Herrera, Victor S Aruana, Ernesto Calderon Martinez. Assessing the Predictive Factors for Bleeding in Esophageal Variceal Disease: A Systematic ReviewCureus 2023;  doi: 10.7759/cureus.48954
3
Yu-Jie Peng, Xin Liu, Ying Liu, Xue Tang, Qi-Peng Zhao, Yong Du. Computed tomography-based multi-organ radiomics nomogram model for predicting the risk of esophagogastric variceal bleeding in cirrhosisWorld Journal of Gastroenterology 2024; 30(36): 4044-4056 doi: 10.3748/wjg.v30.i36.4044
4
Tong Lu, Yu Fang, Haonan Liu, Chong Chen, Taotao Li, Miao Lu, Daqing Song. Comparison of Machine Learning and Logic Regression Algorithms for Predicting Lymph Node Metastasis in Patients with Gastric Cancer: A two-Center StudyTechnology in Cancer Research & Treatment 2024; 23 doi: 10.1177/15330338231222331
5
Jing Xu, Lin Tan, Ning Jiang, Fengcheng Li, Jinling Wang, Beibei Wang, Shasha Li. Assessment of nomogram model for the prediction of esophageal variceal hemorrhage in hepatitis B-induced hepatic cirrhosisEuropean Journal of Gastroenterology & Hepatology 2024; 36(6): 758 doi: 10.1097/MEG.0000000000002750
6
Chunli Li, Xiaoming Zhang, Yuan Gao, Xiaoli Yin, Le Lu, Ling Zhang, Ke Yan, Yu Shi. Medical Image Computing and Computer Assisted Intervention – MICCAI 2024Lecture Notes in Computer Science 2024; 15005: 349 doi: 10.1007/978-3-031-72086-4_33
7
Sahib Singh, Saurabh Chandan, Rakesh Vinayek, Ganesh Aswath, Antonio Facciorusso, Marcello Maida. Comprehensive approach to esophageal variceal bleeding: From prevention to treatmentWorld Journal of Gastroenterology 2024; 30(43): 4602-4608 doi: 10.3748/wjg.v30.i43.4602
8
Tong Lu, Miao Lu, Dong Wu, Yuan-Yuan Ding, Hao-Nan Liu, Tao-Tao Li, Da-Qing Song. Predictive value of machine learning models for lymph node metastasis in gastric cancer: A two-center studyWorld Journal of Gastrointestinal Surgery 2024; 16(1): 85-94 doi: 10.4240/wjgs.v16.i1.85
9
Jih-An Cheng, Yu-Chun Lin, Yenpo Lin, Ren-Chin Wu, Hsin-Ying Lu, Lan-Yan Yang, Hsin-Ju Chiang, Yu-Hsiang Juan, Ying-Chieh Lai, Gigin Lin. Machine Learning Radiomics Signature for Differentiating Lymphoma versus Benign Splenomegaly on CTDiagnostics 2023; 13(24): 3632 doi: 10.3390/diagnostics13243632
10
Zhichun Li, Qian He, Xiao Yang, Tingting Zhu, Xinghui Li, Yan Lei, Wei Tang, Song Peng. A clinical-radiomics nomogram for the prediction of the risk of upper gastrointestinal bleeding in patients with decompensated cirrhosisFrontiers in Medicine 2024; 11 doi: 10.3389/fmed.2024.1308435
11
Jieyu Peng, Xinyi Zeng, Shu Huang, Han Zhang, Huifang Xia, Kang Zou, Wei Zhang, Xiaomin Shi, Lei Shi, Xiaolin Zhong, Muhan Lü, Yan Peng, Xiaowei Tang. Trends of hospitalisation among new admission inpatients with oesophagogastric variceal bleeding in cirrhosis from 2014 to 2019 in the Affiliated Hospital of Southwest Medical University: a single-centre time-series analysisBMJ Open 2024; 14(2): e074608 doi: 10.1136/bmjopen-2023-074608
12
Salvatore Claudio Fanni, Maria Febi, Roberto Francischello, Francesca Pia Caputo, Ilaria Ambrosini, Giacomo Sica, Lorenzo Faggioni, Salvatore Masala, Michele Tonerini, Mariano Scaglione, Dania Cioni, Emanuele Neri. Radiomics Applications in Spleen Imaging: A Systematic Review and Methodological Quality AssessmentDiagnostics 2023; 13(16): 2623 doi: 10.3390/diagnostics13162623