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Cited by in CrossRef
For: Zhang YH, Guo LJ, Yuan XL, Hu B. Artificial intelligence-assisted esophageal cancer management: Now and future. World J Gastroenterol 2020; 26(35): 5256-5271 [PMID: 32994686 DOI: 10.3748/wjg.v26.i35.5256]
URL: https://www.wjgnet.com/1007-9327/full/v26/i35/5256.htm
Number Citing Articles
1
Hsu-Heng Yen, Ping-Yu Wu, Pei-Yuan Su, Chia-Wei Yang, Yang-Yuan Chen, Mei-Fen Chen, Wen-Chen Lin, Cheng-Lun Tsai, Kang-Ping Lin. Performance Comparison of the Deep Learning and the Human Endoscopist for Bleeding Peptic Ulcer DiseaseJournal of Medical and Biological Engineering 2021; 41(4): 504 doi: 10.1007/s40846-021-00608-0
2
Yu Yang, Yu-Xuan Li, Ren-Qi Yao, Xiao-Hui Du, Chao Ren. Artificial intelligence in small intestinal diseases: Application and prospectsWorld Journal of Gastroenterology 2021; 27(25): 3734-3747 doi: 10.3748/wjg.v27.i25.3734
3
Khalid M Bhatti, Zubair S Khanzada, Matta Kuzman, Syed M Ali, Syed Y Iftikhar, Peter Small. Diagnostic Performance of Artificial Intelligence-Based Models for the Detection of Early Esophageal Cancers in Barret’s Esophagus: A Meta-Analysis of Patient-Based StudiesCureus 2021;  doi: 10.7759/cureus.15447
4
Rhiannon McShane, Swati Arya, Alan J. Stewart, Peter D. Caie, Mark Bates. Prognostic features of the tumour microenvironment in oesophageal adenocarcinomaBiochimica et Biophysica Acta (BBA) - Reviews on Cancer 2021; 1876(2): 188598 doi: 10.1016/j.bbcan.2021.188598
5
Yong Liu. Artificial intelligence-assisted endoscopic detection of esophageal neoplasia in early stage: The next step?World Journal of Gastroenterology 2021; 27(14): 1392-1405 doi: 10.3748/wjg.v27.i14.1392
6
Philip H. Pucher, Bas P.L. Wijnhoven, Timothy J. Underwood, John V. Reynolds, Andrew R. Davies. Thinking through the multimodal treatment of localized oesophageal cancer: the point of view of the surgeonCurrent Opinion in Oncology 2021; 33(4): 353 doi: 10.1097/CCO.0000000000000751