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Cited by in F6Publishing
For: Niu PH, Zhao LL, Wu HL, Zhao DB, Chen YT. Artificial intelligence in gastric cancer: Application and future perspectives. World J Gastroenterol 2020; 26(36): 5408-5419 [PMID: 33024393 DOI: 10.3748/wjg.v26.i36.5408] [Cited by in CrossRef: 12] [Cited by in F6Publishing: 7] [Article Influence: 6.0] [Reference Citation Analysis]
Number Citing Articles
1 Yoshida H, Kiyuna T. Requirements for implementation of artificial intelligence in the practice of gastrointestinal pathology. World J Gastroenterol 2021; 27(21): 2818-2833 [PMID: 34135556 DOI: 10.3748/wjg.v27.i21.2818] [Reference Citation Analysis]
2 Yang X, Zheng Y, Liu L, Huang J, Wang F, Zhang J. Progress on the study of the anticancer effects of artesunate. Oncol Lett 2021;22:750. [PMID: 34539854 DOI: 10.3892/ol.2021.13011] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
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5 Wei J, Wang R, Lu Y, He S, Yuan B, Zhang J, Ding Y. Flotillin-1 promotes progression and dampens chemosensitivity to cisplatin in gastric cancer via ERK and AKT signaling pathways. Eur J Pharmacol 2021;:174631. [PMID: 34774850 DOI: 10.1016/j.ejphar.2021.174631] [Reference Citation Analysis]
6 El-Nakeep S, El-Nakeep M. Artificial intelligence for cancer detection in upper gastrointestinal endoscopy, current status, and future aspirations. Artif Intell Gastroenterol 2021; 2(5): 124-132 [DOI: 10.35712/aig.v2.i5.124] [Reference Citation Analysis]
7 Yang Y, Li YX, Yao RQ, Du XH, Ren C. Artificial intelligence in small intestinal diseases: Application and prospects. World J Gastroenterol 2021; 27(25): 3734-3747 [PMID: 34321840 DOI: 10.3748/wjg.v27.i25.3734] [Reference Citation Analysis]
8 Alpsoy A, Yavuz A, Elpek GO. Artificial intelligence in pathological evaluation of gastrointestinal cancers. Artif Intell Gastroenterol 2021; 2(6): 141-156 [DOI: 10.35712/aig.v2.i6.141] [Reference Citation Analysis]
9 Liu Y. Artificial intelligence-assisted endoscopic detection of esophageal neoplasia in early stage: The next step? World J Gastroenterol 2021; 27(14): 1392-1405 [PMID: 33911463 DOI: 10.3748/wjg.v27.i14.1392] [Reference Citation Analysis]
10 Hasic Telalovic J, Pillozzi S, Fabbri R, Laffi A, Lavacchi D, Rossi V, Dreoni L, Spada F, Fazio N, Amedei A, Iadanza E, Antonuzzo L. A Machine Learning Decision Support System (DSS) for Neuroendocrine Tumor Patients Treated with Somatostatin Analog (SSA) Therapy. Diagnostics (Basel) 2021;11:804. [PMID: 33925256 DOI: 10.3390/diagnostics11050804] [Reference Citation Analysis]
11 Li Q, Liu BR. Application of artificial intelligence-assisted endoscopic detection of early esophageal cancer. Shijie Huaren Xiaohua Zazhi 2021; 29(24): 1389-1395 [DOI: 10.11569/wcjd.v29.i24.1389] [Reference Citation Analysis]
12 Chidambaram S, Sounderajah V, Maynard N, Markar SR. Diagnostic Performance of Artificial Intelligence-Centred Systems in the Diagnosis and Postoperative Surveillance of Upper Gastrointestinal Malignancies Using Computed Tomography Imaging: A Systematic Review and Meta-Analysis of Diagnostic Accuracy. Ann Surg Oncol 2021. [PMID: 34762214 DOI: 10.1245/s10434-021-10882-6] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
13 Nawab K, Athwani R, Naeem A, Hamayun M, Wazir M. A Review of Applications of Artificial Intelligence in Gastroenterology. Cureus 2021;13:e19235. [PMID: 34877212 DOI: 10.7759/cureus.19235] [Reference Citation Analysis]
14 Yan T, Wong PK, Qin YY. Deep learning for diagnosis of precancerous lesions in upper gastrointestinal endoscopy: A review. World J Gastroenterol 2021; 27(20): 2531-2544 [PMID: 34092974 DOI: 10.3748/wjg.v27.i20.2531] [Reference Citation Analysis]