BPG is committed to discovery and dissemination of knowledge
Cited by in F6Publishing
For: Yang J, Guo X, Ou X, Zhang W, Ma X. Discrimination of Pancreatic Serous Cystadenomas From Mucinous Cystadenomas With CT Textural Features: Based on Machine Learning. Front Oncol. 2019;9:494. [PMID: 31245294 DOI: 10.3389/fonc.2019.00494] [Cited by in Crossref: 21] [Cited by in F6Publishing: 22] [Article Influence: 7.0] [Reference Citation Analysis]
Number Citing Articles
1 Jiang X, Zou X, Sun J, Zheng A, Su C. A Nomogram Based on Radiomics with Mammography Texture Analysis for the Prognostic Prediction in Patients with Triple-Negative Breast Cancer. Contrast Media Mol Imaging 2020;2020:5418364. [PMID: 32922222 DOI: 10.1155/2020/5418364] [Reference Citation Analysis]
2 Karmazanovsky G, Gruzdev I, Tikhonova V, Kondratyev E, Revishvili A. Computed tomography-based radiomics approach in pancreatic tumors characterization. Radiol Med 2021. [PMID: 34386897 DOI: 10.1007/s11547-021-01405-0] [Reference Citation Analysis]
3 Chen X, Huang Y, He L, Zhang T, Zhang L, Ding H. CT-Based Radiomics to Differentiate Pelvic Rhabdomyosarcoma From Yolk Sac Tumors in Children. Front Oncol 2020;10:584272. [PMID: 33330062 DOI: 10.3389/fonc.2020.584272] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 1.5] [Reference Citation Analysis]
4 Bian Y, Jiang H, Ma C, Cao K, Fang X, Li J, Wang L, Zheng J, Lu J. Performance of CT-based radiomics in diagnosis of superior mesenteric vein resection margin in patients with pancreatic head cancer. Abdom Radiol (NY). 2020;45:759-773. [PMID: 31932878 DOI: 10.1007/s00261-019-02401-9] [Cited by in Crossref: 5] [Cited by in F6Publishing: 3] [Article Influence: 5.0] [Reference Citation Analysis]
5 Ren S, Zhao R, Zhang J, Guo K, Gu X, Duan S, Wang Z, Chen R. Diagnostic accuracy of unenhanced CT texture analysis to differentiate mass-forming pancreatitis from pancreatic ductal adenocarcinoma. Abdom Radiol (NY) 2020;45:1524-33. [PMID: 32279101 DOI: 10.1007/s00261-020-02506-6] [Cited by in Crossref: 10] [Cited by in F6Publishing: 7] [Article Influence: 5.0] [Reference Citation Analysis]
6 Wang X, Chung WY, Correa E, Zhu Y, Issa E, Dennison AR. The integration of artificial intelligence models to augment imaging modalities in pancreatic cancer. Journal of Pancreatology 2020;3:173-80. [DOI: 10.1097/jp9.0000000000000056] [Cited by in Crossref: 1] [Article Influence: 0.5] [Reference Citation Analysis]
7 Machicado JD, Koay EJ, Krishna SG. Radiomics for the Diagnosis and Differentiation of Pancreatic Cystic Lesions. Diagnostics (Basel) 2020;10:E505. [PMID: 32708348 DOI: 10.3390/diagnostics10070505] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.5] [Reference Citation Analysis]
8 Wang Y, Zhang L, Qi L, Yi X, Li M, Zhou M, Chen D, Xiao Q, Wang C, Pang Y, Xu J, Deng H, Liu L, Guan X. Machine Learning: Applications and Advanced Progresses of Radiomics in Endocrine Neoplasms. J Oncol 2021;2021:8615450. [PMID: 34671399 DOI: 10.1155/2021/8615450] [Reference Citation Analysis]
9 Chen S, Ren S, Guo K, Daniels MJ, Wang Z, Chen R. Preoperative differentiation of serous cystic neoplasms from mucin-producing pancreatic cystic neoplasms using a CT-based radiomics nomogram. Abdom Radiol (NY) 2021;46:2637-46. [PMID: 33558952 DOI: 10.1007/s00261-021-02954-8] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
10 de la Pinta C. Radiomics in pancreatic cancer for oncologist: Present and future. Hepatobiliary Pancreat Dis Int 2021:S1499-3872(21)00231-9. [PMID: 34961674 DOI: 10.1016/j.hbpd.2021.12.006] [Reference Citation Analysis]
11 Chu LC, Park S, Kawamoto S, Yuille AL, Hruban RH, Fishman EK. Pancreatic Cancer Imaging: A New Look at an Old Problem. Curr Probl Diagn Radiol 2021;50:540-50. [PMID: 32988674 DOI: 10.1067/j.cpradiol.2020.08.002] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
12 Chen BB. Artificial intelligence in pancreatic disease. Artif Intell Med Imaging 2020; 1(1): 19-30 [DOI: 10.35711/aimi.v1.i1.19] [Reference Citation Analysis]
13 Kröner PT, Engels MM, Glicksberg BS, Johnson KW, Mzaik O, van Hooft JE, Wallace MB, El-Serag HB, Krittanawong C. Artificial intelligence in gastroenterology: A state-of-the-art review. World J Gastroenterol 2021; 27(40): 6794-6824 [PMID: 34790008 DOI: 10.3748/wjg.v27.i40.6794] [Reference Citation Analysis]
14 Ren S, Zhao R, Cui W, Qiu W, Guo K, Cao Y, Duan S, Wang Z, Chen R. Computed Tomography-Based Radiomics Signature for the Preoperative Differentiation of Pancreatic Adenosquamous Carcinoma From Pancreatic Ductal Adenocarcinoma. Front Oncol 2020;10:1618. [PMID: 32984030 DOI: 10.3389/fonc.2020.01618] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
15 Dalal V, Carmicheal J, Dhaliwal A, Jain M, Kaur S, Batra SK. Radiomics in stratification of pancreatic cystic lesions: Machine learning in action. Cancer Lett 2020;469:228-37. [PMID: 31629933 DOI: 10.1016/j.canlet.2019.10.023] [Cited by in Crossref: 20] [Cited by in F6Publishing: 15] [Article Influence: 6.7] [Reference Citation Analysis]
16 Chen PT, Chang D, Wu T, Wu MS, Wang W, Liao WC. Applications of artificial intelligence in pancreatic and biliary diseases. J Gastroenterol Hepatol 2021;36:286-94. [PMID: 33624891 DOI: 10.1111/jgh.15380] [Reference Citation Analysis]
17 Bartoli M, Barat M, Dohan A, Gaujoux S, Coriat R, Hoeffel C, Cassinotto C, Chassagnon G, Soyer P. CT and MRI of pancreatic tumors: an update in the era of radiomics. Jpn J Radiol 2020;38:1111-24. [PMID: 33085029 DOI: 10.1007/s11604-020-01057-6] [Cited by in Crossref: 11] [Cited by in F6Publishing: 10] [Article Influence: 5.5] [Reference Citation Analysis]
18 Xie T, Wang X, Zhang Z, Zhou Z. CT-Based Radiomics Analysis for Preoperative Diagnosis of Pancreatic Mucinous Cystic Neoplasm and Atypical Serous Cystadenomas. Front Oncol 2021;11:621520. [PMID: 34178619 DOI: 10.3389/fonc.2021.621520] [Reference Citation Analysis]
19 Chen HY, Deng XY, Pan Y, Chen JY, Liu YY, Chen WJ, Yang H, Zheng Y, Yang YB, Liu C, Shao GL, Yu RS. Pancreatic Serous Cystic Neoplasms and Mucinous Cystic Neoplasms: Differential Diagnosis by Combining Imaging Features and Enhanced CT Texture Analysis. Front Oncol 2021;11:745001. [PMID: 35004272 DOI: 10.3389/fonc.2021.745001] [Reference Citation Analysis]
20 Steinacker JP, Steinacker-Stanescu N, Ettrich T, Kornmann M, Kneer K, Beer A, Beer M, Schmidt SA. Computed Tomography-Based Tumor Heterogeneity Analysis Reveals Differences in a Cohort with Advanced Pancreatic Carcinoma under Palliative Chemotherapy. Visc Med 2021;37:77-83. [PMID: 33718486 DOI: 10.1159/000506656] [Reference Citation Analysis]
21 Rosemurgy AS, Ross S, Luberice K, Browning H, Sucandy I. Robotic Pancreatic Surgery for Solid, Cystic, and Mixed Lesions. Surg Clin North Am 2020;100:303-36. [PMID: 32169182 DOI: 10.1016/j.suc.2019.12.006] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
22 Shao C, Feng X, Yu J, Meng Y, Liu F, Zhang H, Fang X, Li J, Wang L, Jiang H, Lu J, Bian Y. A nomogram for predicting pancreatic mucinous cystic neoplasm and serous cystic neoplasm. Abdom Radiol (NY) 2021;46:3963-73. [PMID: 33748881 DOI: 10.1007/s00261-021-03038-3] [Reference Citation Analysis]
23 Han X, Yang J, Luo J, Chen P, Zhang Z, Alu A, Xiao Y, Ma X. Application of CT-Based Radiomics in Discriminating Pancreatic Cystadenomas From Pancreatic Neuroendocrine Tumors Using Machine Learning Methods. Front Oncol 2021;11:606677. [PMID: 34367940 DOI: 10.3389/fonc.2021.606677] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
24 Gao J, Han F, Wang X, Duan S, Zhang J. Multi-Phase CT-Based Radiomics Nomogram for Discrimination Between Pancreatic Serous Cystic Neoplasm From Mucinous Cystic Neoplasm. Front Oncol 2021;11:699812. [PMID: 34926238 DOI: 10.3389/fonc.2021.699812] [Reference Citation Analysis]
25 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: 2] [Article Influence: 1.0] [Reference Citation Analysis]
26 Schlanger D, Graur F, Popa C, Moiș E, Al Hajjar N. The role of artificial intelligence in pancreatic surgery: a systematic review. Updates Surg 2022. [PMID: 35237939 DOI: 10.1007/s13304-022-01255-z] [Reference Citation Analysis]