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Cited by in F6Publishing
For: Cheng NM, Hsieh CE, Fang YD, Liao CT, Ng SH, Wang HM, Chou WC, Lin CY, Yen TC. Development and validation of a prognostic model incorporating [18F]FDG PET/CT radiomics for patients with minor salivary gland carcinoma. EJNMMI Res 2020;10:74. [PMID: 32632638 DOI: 10.1186/s13550-020-00631-3] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
Number Citing Articles
1 Piñeiro-Fiel M, Moscoso A, Pubul V, Ruibal Á, Silva-Rodríguez J, Aguiar P. A Systematic Review of PET Textural Analysis and Radiomics in Cancer. Diagnostics (Basel) 2021;11:380. [PMID: 33672285 DOI: 10.3390/diagnostics11020380] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 4.0] [Reference Citation Analysis]
2 Zhang MH, Hasse A, Carroll T, Pearson AT, Cipriani NA, Ginat DT. Differentiating low and high grade mucoepidermoid carcinoma of the salivary glands using CT radiomics. Gland Surg 2021;10:1646-54. [PMID: 34164309 DOI: 10.21037/gs-20-830] [Reference Citation Analysis]
3 Guo R, Hu X, Song H, Xu P, Xu H, Rominger A, Lin X, Menze B, Li B, Shi K. Weakly supervised deep learning for determining the prognostic value of 18F-FDG PET/CT in extranodal natural killer/T cell lymphoma, nasal type. Eur J Nucl Med Mol Imaging 2021;48:3151-61. [PMID: 33611614 DOI: 10.1007/s00259-021-05232-3] [Reference Citation Analysis]