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Cited by in CrossRef
For: Kim JH, Nam SJ, Park SC. Usefulness of artificial intelligence in gastric neoplasms. World J Gastroenterol 2021; 27(24): 3543-3555 [PMID: 34239268 DOI: 10.3748/wjg.v27.i24.3543]
URL: https://www.wjgnet.com/1007-9327/full/v27/i24/3543.htm
Number Citing Articles
Luyang Jie, Pengchen Liang, Ziyuan Zhao, Jianguo Chen, Qing Chang, Zeng Zeng. ADAN: An Adversarial Domain Adaptation Neural Network for Early Gastric Cancer Prediction2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) 2022; : 2169 doi: 10.1109/EMBC48229.2022.9871952
Athanasios G. Pantelis, Panagiota A. Panagopoulou, Dimitris P. Lapatsanis. Artificial Intelligence and Machine Learning in the Diagnosis and Management of Gastroenteropancreatic Neuroendocrine Neoplasms—A Scoping ReviewDiagnostics 2022; 12(4): 874 doi: 10.3390/diagnostics12040874
真 徐. Advances in Endoscopic Diagnosis of Early Gastric CancerAdvances in Clinical Medicine 2023; 13(04): 6577 doi: 10.12677/ACM.2023.134922
晨阳 郭. Application and Prospect of Artificial Intelligence Technology in Gastrointestinal TumorsAdvances in Clinical Medicine 2022; 12(11): 10497 doi: 10.12677/ACM.2022.12111512
Peng-fei Lyu, Yu Wang, Qing-Xiang Meng, Ping-ming Fan, Ke Ma, Sha Xiao, Xun-chen Cao, Guang-Xun Lin, Si-yuan Dong. Mapping intellectual structures and research hotspots in the application of artificial intelligence in cancer: A bibliometric analysisFrontiers in Oncology 2022; 12 doi: 10.3389/fonc.2022.955668