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Cited by in F6Publishing

For:	Yu H, Huang Z, Li M, Wei Y, Zhang L, Yang C, Zhang Y, Song B. Differential Diagnosis of Nonhypervascular Pancreatic Neuroendocrine Neoplasms From Pancreatic Ductal Adenocarcinomas, Based on Computed Tomography Radiological Features and Texture Analysis. Acad Radiol 2020;27:332-41. [PMID: 31495760 DOI: 10.1016/j.acra.2019.06.012] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.3] [Reference Citation Analysis]

For:

Yu H, Huang Z, Li M, Wei Y, Zhang L, Yang C, Zhang Y, Song B. Differential Diagnosis of Nonhypervascular Pancreatic Neuroendocrine Neoplasms From Pancreatic Ductal Adenocarcinomas, Based on Computed Tomography Radiological Features and Texture Analysis. Acad Radiol 2020;27:332-41. [PMID: 31495760 DOI: 10.1016/j.acra.2019.06.012] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.3] [Reference Citation Analysis]

Number	Citing Articles
1	Zeng P, Ma L, Liu J, Song Z, Liu J, Yuan H. The diagnostic value of intravoxel incoherent motion diffusion-weighted imaging for distinguishing nonhypervascular pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas. European Journal of Radiology 2022;150:110261. [DOI: 10.1016/j.ejrad.2022.110261] [Reference Citation Analysis]
2	Gerbaudo VH, Latif MA. A Step Forward in PET-Based Quantitation of G3 Neuroendocrine Tumor Aggressiveness - The FDZ Score…. Acad Radiol 2022:S1076-6332(22)00140-4. [PMID: 35365399 DOI: 10.1016/j.acra.2022.03.001] [Reference Citation Analysis]
3	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]
4	Virarkar M, Wong VK, Morani AC, Tamm EP, Bhosale P. Update on quantitative radiomics of pancreatic tumors. Abdom Radiol (NY) 2021. [PMID: 34292365 DOI: 10.1007/s00261-021-03216-3] [Reference Citation Analysis]
5	Budigi B, Oliphant M, Itri J. Pancreatic Adenocarcinoma: Diagnostic Errors, Contributing Factors and Solutions. Acad Radiol 2021:S1076-6332(21)00497-9. [PMID: 34838452 DOI: 10.1016/j.acra.2021.10.025] [Reference Citation Analysis]
6	Bezzi C, Mapelli P, Presotto L, Neri I, Scifo P, Savi A, Bettinardi V, Partelli S, Gianolli L, Falconi M, Picchio M. Radiomics in pancreatic neuroendocrine tumors: methodological issues and clinical significance. Eur J Nucl Med Mol Imaging 2021. [PMID: 33835220 DOI: 10.1007/s00259-021-05338-8] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
7	Lee H, Nakamoto R, Moore SE, Pantel AR, Eads JR, Aparici CM, Pryma DA. Combined Quantification of ¹⁸F-FDG and ⁶⁸Ga-DOTATATE PET/CT for Prognosis in High-Grade Gastroenteropancreatic Neuroendocrine Neoplasms. Acad Radiol 2021:S1076-6332(21)00462-1. [PMID: 34836776 DOI: 10.1016/j.acra.2021.10.004] [Reference Citation Analysis]
8	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]