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Cited by in F6Publishing
For: Walczak S, Velanovich V. An Evaluation of Artificial Neural Networks in Predicting Pancreatic Cancer Survival. J Gastrointest Surg. 2017;21:1606-1612. [PMID: 28776157 DOI: 10.1007/s11605-017-3518-7] [Cited by in Crossref: 16] [Cited by in F6Publishing: 11] [Article Influence: 4.0] [Reference Citation Analysis]
Number Citing Articles
1 Bradley A, van der Meer R, McKay C. Personalized Pancreatic Cancer Management: A Systematic Review of How Machine Learning Is Supporting Decision-making. Pancreas 2019;48:598-604. [PMID: 31090660 DOI: 10.1097/MPA.0000000000001312] [Cited by in Crossref: 6] [Cited by in F6Publishing: 2] [Article Influence: 6.0] [Reference Citation Analysis]
2 Gorris M, Hoogenboom SA, Wallace MB, van Hooft JE. Artificial intelligence for the management of pancreatic diseases. Dig Endosc 2021;33:231-41. [PMID: 33065754 DOI: 10.1111/den.13875] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
3 Bradley A, Van Der Meer R, McKay CJ. A systematic review of methodological quality of model development studies predicting prognostic outcome for resectable pancreatic cancer. BMJ Open 2019;9:e027192. [PMID: 31439598 DOI: 10.1136/bmjopen-2018-027192] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 2.5] [Reference Citation Analysis]
4 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]
5 Ao C, Jin S, Ding H, Zou Q, Yu L. Application and Development of Artificial Intelligence and Intelligent Disease Diagnosis. Curr Pharm Des 2020;26:3069-75. [PMID: 32228416 DOI: 10.2174/1381612826666200331091156] [Cited by in Crossref: 7] [Cited by in F6Publishing: 4] [Article Influence: 7.0] [Reference Citation Analysis]
6 Laoveeravat P, Abhyankar PR, Brenner AR, Gabr MM, Habr FG, Atsawarungruangkit A. Artificial intelligence for pancreatic cancer detection: Recent development and future direction. AIG 2021;2:56-68. [DOI: 10.35712/aig.v2.i2.56] [Reference Citation Analysis]
7 Oh TK, Do SH, Yoon YS, Song IA. Association Between Opioid Use and Survival Time in Patients With Unresectable Pancreatic Cancer: 10 Years of Clinical Experience. Pancreas 2018;47:837-42. [PMID: 29939907 DOI: 10.1097/MPA.0000000000001094] [Cited by in Crossref: 11] [Cited by in F6Publishing: 5] [Article Influence: 5.5] [Reference Citation Analysis]
8 Livingstone D, Talai AS, Chau J, Forkert ND. Building an Otoscopic screening prototype tool using deep learning. J Otolaryngol Head Neck Surg 2019;48:66. [PMID: 31771647 DOI: 10.1186/s40463-019-0389-9] [Cited by in Crossref: 12] [Cited by in F6Publishing: 8] [Article Influence: 6.0] [Reference Citation Analysis]
9 Ito Y, Unagami M, Yamabe F, Mitsui Y, Nakajima K, Nagao K, Kobayashi H. A method for utilizing automated machine learning for histopathological classification of testis based on Johnsen scores. Sci Rep 2021;11:9962. [PMID: 33967273 DOI: 10.1038/s41598-021-89369-z] [Reference Citation Analysis]
10 Liu SL, Li S, Guo YT, Zhou YP, Zhang ZD, Lu Y. Establishment and application of an artificial intelligence diagnosis system for pancreatic cancer with a faster region-based convolutional neural network. Chin Med J (Engl). 2019;132:2795-2803. [PMID: 31856050 DOI: 10.1097/cm9.0000000000000544] [Cited by in Crossref: 18] [Cited by in F6Publishing: 10] [Article Influence: 18.0] [Reference Citation Analysis]
11 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]