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Cited by in F6Publishing
For: Momeni-Boroujeni A, Yousefi E, Somma J. Computer-assisted cytologic diagnosis in pancreatic FNA: An application of neural networks to image analysis. Cancer Cytopathol. 2017;125:926-933. [PMID: 28885766 DOI: 10.1002/cncy.21915] [Cited by in Crossref: 9] [Cited by in F6Publishing: 11] [Article Influence: 2.3] [Reference Citation Analysis]
Number Citing Articles
1 Sanghvi AB, Allen EZ, Callenberg KM, Pantanowitz L. Performance of an artificial intelligence algorithm for reporting urine cytopathology. Cancer Cytopathol 2019;127:658-66. [PMID: 31412169 DOI: 10.1002/cncy.22176] [Cited by in Crossref: 19] [Cited by in F6Publishing: 14] [Article Influence: 9.5] [Reference Citation Analysis]
2 Mendoza Ladd A, Diehl DL. Artificial intelligence for early detection of pancreatic adenocarcinoma: The future is promising. World J Gastroenterol 2021;27:1283-95. [PMID: 33833482 DOI: 10.3748/wjg.v27.i13.1283] [Reference Citation Analysis]
3 Lin H, Xue X, Wang X, Dang S, Gu M. Application of artificial intelligence for the diagnosis, treatment, and prognosis of pancreatic cancer. AIG 2020;1:19-29. [DOI: 10.35712/aig.v1.i1.19] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
4 Parasher G, Wong M, Rawat M. Evolving role of artificial intelligence in gastrointestinal endoscopy. World J Gastroenterol. 2020;26:7287-7298. [PMID: 33362384 DOI: 10.3748/wjg.v26.i46.7287] [Cited by in CrossRef: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
5 Guan Q, Wan X, Lu H, Ping B, Li D, Wang L, Zhu Y, Wang Y, Xiang J. Deep convolutional neural network Inception-v3 model for differential diagnosing of lymph node in cytological images: a pilot study. Ann Transl Med 2019;7:307. [PMID: 31475177 DOI: 10.21037/atm.2019.06.29] [Cited by in Crossref: 5] [Cited by in F6Publishing: 2] [Article Influence: 2.5] [Reference Citation Analysis]
6 Xu J, Jing M, Wang S, Yang C, Chen X. A review of medical image detection for cancers in digestive system based on artificial intelligence. Expert Rev Med Devices. 2019;16:877-889. [PMID: 31530047 DOI: 10.1080/17434440.2019.1669447] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 2.5] [Reference Citation Analysis]
7 Landau MS, Pantanowitz L. Artificial intelligence in cytopathology: a review of the literature and overview of commercial landscape. Journal of the American Society of Cytopathology 2019;8:230-41. [DOI: 10.1016/j.jasc.2019.03.003] [Cited by in Crossref: 25] [Cited by in F6Publishing: 18] [Article Influence: 12.5] [Reference Citation Analysis]
8 Akshintala VS, Khashab MA. Artificial intelligence in pancreaticobiliary endoscopy. J Gastroenterol Hepatol. 2021;36:25-30. [PMID: 33448514 DOI: 10.1111/jgh.15343] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
9 Guan Q, Wang Y, Ping B, Li D, Du J, Qin Y, Lu H, Wan X, Xiang J. Deep convolutional neural network VGG-16 model for differential diagnosing of papillary thyroid carcinomas in cytological images: a pilot study. J Cancer 2019;10:4876-82. [PMID: 31598159 DOI: 10.7150/jca.28769] [Cited by in Crossref: 30] [Cited by in F6Publishing: 13] [Article Influence: 15.0] [Reference Citation Analysis]
10 Cazacu IM, Udristoiu A, Gruionu LG, Iacob A, Gruionu G, Saftoiu A. Artificial intelligence in pancreatic cancer: Toward precision diagnosis. Endosc Ultrasound. 2019;8:357-359. [PMID: 31854344 DOI: 10.4103/eus.eus_76_19] [Cited by in Crossref: 10] [Cited by in F6Publishing: 7] [Article Influence: 5.0] [Reference Citation Analysis]
11 Xia R, Boroujeni AM, Shea S, Pan Y, Agrawal R, Yousefi E, Fiel MI, Haseeb MA, Gupta R. Diagnosis of Liver Neoplasms by Computational and Statistical Image Analysis. Gastroenterology Res 2019;12:288-98. [PMID: 31803308 DOI: 10.14740/gr1210] [Cited by in F6Publishing: 1] [Reference Citation Analysis]