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For: Norton ID, Zheng Y, Wiersema MS, Greenleaf J, Clain JE, Dimagno EP. Neural network analysis of EUS images to differentiate between pancreatic malignancy and pancreatitis. Gastrointest Endosc. 2001;54:625-629. [PMID: 11677484 DOI: 10.1067/mge.2001.118644] [Cited by in Crossref: 51] [Cited by in F6Publishing: 43] [Article Influence: 2.6] [Reference Citation Analysis]
Number Citing Articles
1 Zhang MM, Yang H, Jin ZD, Yu JG, Cai ZY, Li ZS. Differential diagnosis of pancreatic cancer from normal tissue with digital imaging processing and pattern recognition based on a support vector machine of EUS images. Gastrointest Endosc. 2010;72:978-985. [PMID: 20855062 DOI: 10.1016/j.gie.2010.06.042] [Cited by in Crossref: 36] [Cited by in F6Publishing: 32] [Article Influence: 3.3] [Reference Citation Analysis]
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6 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]
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11 Nguyen VX, Nguyen CC, Li B, Das A. Digital Image Analysis Is a Useful Adjunct to Endoscopic Ultrasonographic Diagnosis of Subepithelial Lesions of the Gastrointestinal Tract. Journal of Ultrasound in Medicine 2010;29:1345-51. [DOI: 10.7863/jum.2010.29.9.1345] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 0.6] [Reference Citation Analysis]
12 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]
13 DiMagno MJ, DiMagno EP. Chronic pancreatitis. Curr Opin Gastroenterol 2005;21:544-54. [PMID: 16093768 DOI: 10.1097/01.mog.0000175543.42582.55] [Cited by in Crossref: 27] [Cited by in F6Publishing: 19] [Article Influence: 1.7] [Reference Citation Analysis]
14 Marya NB, Powers PD, Chari ST, Gleeson FC, Leggett CL, Abu Dayyeh BK, Chandrasekhara V, Iyer PG, Majumder S, Pearson RK, Petersen BT, Rajan E, Sawas T, Storm AC, Vege SS, Chen S, Long Z, Hough DM, Mara K, Levy MJ. Utilisation of artificial intelligence for the development of an EUS-convolutional neural network model trained to enhance the diagnosis of autoimmune pancreatitis. Gut. 2021;70:1335-1344. [PMID: 33028668 DOI: 10.1136/gutjnl-2020-322821] [Cited by in Crossref: 9] [Cited by in F6Publishing: 7] [Article Influence: 9.0] [Reference Citation Analysis]
15 Săftoiu A, Vilmann P, Gorunescu F, Janssen J, Hocke M, Larsen M, Iglesias–garcia J, Arcidiacono P, Will U, Giovannini M, Dietrich CF, Havre R, Gheorghe C, Mckay C, Gheonea DI, Ciurea T. Efficacy of an Artificial Neural Network–Based Approach to Endoscopic Ultrasound Elastography in Diagnosis of Focal Pancreatic Masses. Clinical Gastroenterology and Hepatology 2012;10:84-90.e1. [DOI: 10.1016/j.cgh.2011.09.014] [Cited by in Crossref: 88] [Cited by in F6Publishing: 69] [Article Influence: 9.8] [Reference Citation Analysis]
16 Bartosch-Härlid A, Andersson B, Aho U, Nilsson J, Andersson R. Artificial neural networks in pancreatic disease. Br J Surg. 2008;95:817-826. [PMID: 18551536 DOI: 10.1002/bjs.6239] [Cited by in Crossref: 40] [Cited by in F6Publishing: 28] [Article Influence: 3.1] [Reference Citation Analysis]
17 Papanikolaou IS, Adler A, Neumann U, Neuhaus P, Rösch T. Endoscopic ultrasound in pancreatic disease--its influence on surgical decision-making. An update 2008. Pancreatology. 2009;9:55-65. [PMID: 19077455 DOI: 10.1159/000178875] [Cited by in Crossref: 18] [Cited by in F6Publishing: 16] [Article Influence: 1.4] [Reference Citation Analysis]
18 Ahmad OF, Stassen P, Webster GJ. Artificial intelligence in biliopancreatic endoscopy: Is there any role? Best Pract Res Clin Gastroenterol. 2021;52-53:101724. [PMID: 34172251 DOI: 10.1016/j.bpg.2020.101724] [Cited by in Crossref: 2] [Article Influence: 2.0] [Reference Citation Analysis]
19 Tang S, Huang G, Liu J, Liu T, Treven L, Song S, Zhang C, Pan L, Zhang T. Usefulness of 18F-FDG PET, combined FDG-PET/CT and EUS in diagnosing primary pancreatic carcinoma: a meta-analysis. Eur J Radiol. 2011;78:142-150. [PMID: 19854016 DOI: 10.1016/j.ejrad.2009.09.026] [Cited by in Crossref: 75] [Cited by in F6Publishing: 55] [Article Influence: 6.3] [Reference Citation Analysis]
20 Marya NB, Powers PD, Fujii-Lau L, Abu Dayyeh BK, Gleeson FC, Chen S, Long Z, Hough DM, Chandrasekhara V, Iyer PG, Rajan E, Sanchez W, Sawas T, Storm AC, Wang KK, Levy MJ. Application of artificial intelligence using a novel EUS-based convolutional neural network model to identify and distinguish benign and malignant hepatic masses. Gastrointest Endosc 2021;93:1121-1130.e1. [PMID: 32861752 DOI: 10.1016/j.gie.2020.08.024] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
21 Zhang Z, Bai L, Ren P, Hancock ER. High-order graph matching kernel for early carcinoma EUS image classification. Multimed Tools Appl 2016;75:3993-4012. [DOI: 10.1007/s11042-015-3108-1] [Cited by in Crossref: 6] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
22 Tong Z, Liu Y, Ma H, Zhang J, Lin B, Bao X, Xu X, Gu C, Zheng Y, Liu L, Fang W, Deng S, Zhao P. Development, Validation and Comparison of Artificial Neural Network Models and Logistic Regression Models Predicting Survival of Unresectable Pancreatic Cancer. Front Bioeng Biotechnol 2020;8:196. [PMID: 32232040 DOI: 10.3389/fbioe.2020.00196] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 3.0] [Reference Citation Analysis]
23 Faiss S, Lewin JS, Nour SG, Zeitz M, Duerk JL, Wacker FK. Endoscopically inserted endoluminal receiver coil for high-resolution magnetic resonance imaging of the pancreas: Initial results in an animal model. Gastrointest Endosc 2003;57:106-10. [PMID: 12518145 DOI: 10.1067/mge.2003.50] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 0.2] [Reference Citation Analysis]
24 Yusuf TE, Bhutani MS. Differentiating pancreatic cancer from pseudotumorous chronic pancreatitis. Curr Gastroenterol Rep 2002;4:135-9. [DOI: 10.1007/s11894-002-0050-y] [Cited by in F6Publishing: 9] [Reference Citation Analysis]
25 Fusaroli P, Saftoiu A, Mancino MG, Caletti G, Eloubeidi MA. Techniques of image enhancement in EUS (with videos). Gastrointest Endosc. 2011;74:645-655. [PMID: 21679945 DOI: 10.1016/j.gie.2011.03.1246] [Cited by in Crossref: 31] [Cited by in F6Publishing: 27] [Article Influence: 3.1] [Reference Citation Analysis]
26 Pannala R, Krishnan K, Melson J, Parsi MA, Schulman AR, Sullivan S, Trikudanathan G, Trindade AJ, Watson RR, Maple JT, Lichtenstein DR. Artificial intelligence in gastrointestinal endoscopy. VideoGIE. 2020;5:598-613. [PMID: 33319126 DOI: 10.1016/j.vgie.2020.08.013] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 4.0] [Reference Citation Analysis]
27 Loren DE, Seghal CM, Ginsberg GG, Kochman ML. Computer-assisted analysis of lymph nodes detected by EUS in patients with esophageal carcinoma. Gastrointest Endosc. 2002;56:742-746. [PMID: 12397290 DOI: 10.1016/s0016-5107(02)70131-4] [Cited by in Crossref: 15] [Article Influence: 0.8] [Reference Citation Analysis]
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29 Best LM, Rawji V, Pereira SP, Davidson BR, Gurusamy KS. Imaging modalities for characterising focal pancreatic lesions. Cochrane Database Syst Rev 2017;4:CD010213. [PMID: 28415140 DOI: 10.1002/14651858.CD010213.pub2] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 1.8] [Reference Citation Analysis]
30 Mankoo R, Ali AH, Hammoud GM. Use of artificial intelligence in endoscopic ultrasound evaluation of pancreatic pathologies. AIGE 2021;2:89-94. [DOI: 10.37126/aige.v2.i3.89] [Reference Citation Analysis]
31 Zhu J, Wang L, Chu Y, Hou X, Xing L, Kong F, Zhou Y, Wang Y, Jin Z, Li Z. A new descriptor for computer-aided diagnosis of EUS imaging to distinguish autoimmune pancreatitis from chronic pancreatitis. Gastrointest Endosc 2015;82:831-836.e1. [PMID: 25952089 DOI: 10.1016/j.gie.2015.02.043] [Cited by in Crossref: 9] [Cited by in F6Publishing: 6] [Article Influence: 1.5] [Reference Citation Analysis]
32 Bartosch-Härlid A, Andersson R. Diabetes mellitus in pancreatic cancer and the need for diagnosis of asymptomatic disease. Pancreatology. 2010;10:423-428. [PMID: 20720443 DOI: 10.1159/000264676] [Cited by in Crossref: 40] [Cited by in F6Publishing: 34] [Article Influence: 3.6] [Reference Citation Analysis]
33 Kumon RE, Pollack MJ, Faulx AL, Olowe K, Farooq FT, Chen VK, Zhou Y, Wong RC, Isenberg GA, Sivak MV, Chak A, Deng CX. In vivo characterization of pancreatic and lymph node tissue by using EUS spectrum analysis: a validation study. Gastrointest Endosc 2010;71:53-63. [PMID: 19922913 DOI: 10.1016/j.gie.2009.08.027] [Cited by in Crossref: 15] [Cited by in F6Publishing: 13] [Article Influence: 1.3] [Reference Citation Analysis]
34 Xu W, Liu Y, Lu Z, Jin ZD, Hu YH, Yu JG, Li ZS. A new endoscopic ultrasonography image processing method to evaluate the prognosis for pancreatic cancer treated with interstitial brachytherapy. World J Gastroenterol. 2013;19:6479-6484. [PMID: 24151368 DOI: 10.3748/wjg.v19.i38.6479] [Cited by in CrossRef: 9] [Cited by in F6Publishing: 9] [Article Influence: 1.3] [Reference Citation Analysis]
35 Dimagno EP, Dimagno MJ. Endoscopic Ultrasonography: From the Origins to Routine EUS. Dig Dis Sci 2016;61:342-53. [DOI: 10.1007/s10620-015-3999-8] [Cited by in Crossref: 14] [Cited by in F6Publishing: 8] [Article Influence: 2.3] [Reference Citation Analysis]
36 Tonozuka R, Mukai S, Itoi T. The Role of Artificial Intelligence in Endoscopic Ultrasound for Pancreatic Disorders. Diagnostics (Basel). 2020;11. [PMID: 33374181 DOI: 10.3390/diagnostics11010018] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
37 Chen X, Hu Y, Zhang Z, Wang B, Zhang L, Shi F, Chen X, Jiang X. A graph-based approach to automated EUS image layer segmentation and abnormal region detection. Neurocomputing 2019;336:79-91. [DOI: 10.1016/j.neucom.2018.03.083] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
38 DiMagno MJ, DiMagno EP. Chronic pancreatitis. Curr Opin Gastroenterol 2013;29:531-6. [PMID: 23852141 DOI: 10.1097/MOG.0b013e3283639370] [Cited by in Crossref: 15] [Cited by in F6Publishing: 2] [Article Influence: 2.1] [Reference Citation Analysis]
39 Kongkam P, Ang TL, Vu CK, Dy FT, Yasuda K, Rerknimitr R, Varadarajulu S, Dhir V, Chong VH, Zhen DJ. Current status on the diagnosis and evaluation of pancreatic tumor in Asia with particular emphasis on the role of endoscopic ultrasound. J Gastroenterol Hepatol. 2013;28:924-930. [PMID: 23488477 DOI: 10.1111/jgh.12198] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 0.9] [Reference Citation Analysis]
40 Bartell N, Bittner K, Vetter MS, Kothari T, Kaul V, Kothari S. Role of Endoscopic Ultrasound in Detecting Pancreatic Cancer Missed on Cross-Sectional Imaging in Patients Presenting with Pancreatitis: A Retrospective Review. Dig Dis Sci 2019;64:3623-9. [DOI: 10.1007/s10620-019-05807-z] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.5] [Reference Citation Analysis]
41 Bhutani MS. Digital analysis of EUS images: "promising" method, but is it ready for "prime time"? Gastrointest Endosc 2008;67:868-70. [PMID: 18440378 DOI: 10.1016/j.gie.2007.12.061] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 0.5] [Reference Citation Analysis]
42 Das A, Nguyen CC, Li F, Li B. Digital image analysis of EUS images accurately differentiates pancreatic cancer from chronic pancreatitis and normal tissue. Gastrointest Endosc. 2008;67:861-867. [PMID: 18179797 DOI: 10.1016/j.gie.2007.08.036] [Cited by in Crossref: 46] [Cited by in F6Publishing: 44] [Article Influence: 3.5] [Reference Citation Analysis]
43 DiMagno EP, DiMagno MJ. Chronic Pancreatitis: Landmark Papers, Management Decisions, and Future. Pancreas 2016;45:641-50. [PMID: 27077713 DOI: 10.1097/MPA.0000000000000599] [Cited by in Crossref: 23] [Cited by in F6Publishing: 4] [Article Influence: 5.8] [Reference Citation Analysis]