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Cited by in F6Publishing
For: 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]
Number Citing Articles
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2 Gao Y, Lu Y, Li S, Dai Y, Feng B, Han FH, Han JG, He JJ, Li XX, Lin GL, Liu Q, Wang GY, Wang Q, Wang ZN, Wang Z, Wu AW, Wu B, Yang YC, Yao HW, Zhang W, Zhou JP, Hao AM, Zhang ZT; Colorectal Surgery Group of the Surgery Branch in the Chinese Medical Association; Beihang University State Key Laboratory of Virtual Reality Technology and Systems. Chinese guideline for the application of rectal cancer staging recognition systems based on artificial intelligence platforms (2021 edition). Chin Med J (Engl) 2021;134:1261-3. [PMID: 34075899 DOI: 10.1097/CM9.0000000000001483] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Liu S, Zhang Y, Ju Y, Li Y, Kang X, Yang X, Niu T, Xing X, Lu Y. Establishment and Clinical Application of an Artificial Intelligence Diagnostic Platform for Identifying Rectal Cancer Tumor Budding. Front Oncol 2021;11:626626. [PMID: 33763362 DOI: 10.3389/fonc.2021.626626] [Reference Citation Analysis]
4 Ma H, Liu ZX, Zhang JJ, Wu FT, Xu CF, Shen Z, Yu CH, Li YM. Construction of a convolutional neural network classifier developed by computed tomography images for pancreatic cancer diagnosis. World J Gastroenterol. 2020;26:5156-5168. [PMID: 32982116 DOI: 10.3748/wjg.v26.i34.5156] [Cited by in CrossRef: 4] [Cited by in F6Publishing: 3] [Article Influence: 4.0] [Reference Citation Analysis]
5 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]
6 Qiu WR, Chen G, Wu J, Lei J, Xu L, Zhang SH. Analyzing Surgical Treatment of Intestinal Obstruction in Children with Artificial Intelligence. Comput Math Methods Med 2021;2021:6652288. [PMID: 33505514 DOI: 10.1155/2021/6652288] [Reference Citation Analysis]
7 Goyal H, Mann R, Gandhi Z, Perisetti A, Zhang Z, Sharma N, Saligram S, Inamdar S, Tharian B. Application of artificial intelligence in pancreaticobiliary diseases.Ther Adv Gastrointest Endosc. 2021;14:2631774521993059. [PMID: 33644756 DOI: 10.1177/2631774521993059] [Reference Citation Analysis]
8 Enriquez JS, Chu Y, Pudakalakatti S, Hsieh KL, Salmon D, Dutta P, Millward NZ, Lurie E, Millward S, McAllister F, Maitra A, Sen S, Killary A, Zhang J, Jiang X, Bhattacharya PK, Shams S. Hyperpolarized Magnetic Resonance and Artificial Intelligence: Frontiers of Imaging in Pancreatic Cancer. JMIR Med Inform 2021;9:e26601. [PMID: 34137725 DOI: 10.2196/26601] [Reference Citation Analysis]
9 Vogrin M, Trojner T, Kelc R. Artificial intelligence in musculoskeletal oncological radiology. Radiol Oncol 2020;55:1-6. [PMID: 33885240 DOI: 10.2478/raon-2020-0068] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
10 Barat M, Chassagnon G, Dohan A, Gaujoux S, Coriat R, Hoeffel C, Cassinotto C, Soyer P. Artificial intelligence: a critical review of current applications in pancreatic imaging. Jpn J Radiol 2021;39:514-23. [PMID: 33550513 DOI: 10.1007/s11604-021-01098-5] [Reference Citation Analysis]