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Cited by in F6Publishing
For: Teng X, Zhang J, Zwanenburg A, Sun J, Huang Y, Lam S, Zhang Y, Li B, Zhou T, Xiao H, Liu C, Li W, Han X, Ma Z, Li T, Cai J. Building reliable radiomic models using image perturbation. Sci Rep 2022;12:10035. [PMID: 35710850 DOI: 10.1038/s41598-022-14178-x] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
Number Citing Articles
1 Teng X, Zhang J, Ma Z, Zhang Y, Lam S, Li W, Xiao H, Li T, Li B, Zhou T, Ren G, Lee FK, Au K, Lee VH, Chang ATY, Cai J. Improving radiomic model reliability using robust features from perturbations for head-and-neck carcinoma. Front Oncol 2022;12:974467. [DOI: 10.3389/fonc.2022.974467] [Reference Citation Analysis]
2 Wennmann M, Bauer F, Klein A, Chmelik J, Grözinger M, Rotkopf LT, Neher P, Gnirs R, Kurz FT, Nonnenmacher T, Sauer S, Weinhold N, Goldschmidt H, Kleesiek J, Bonekamp D, Weber TF, Delorme S, Maier-Hein K, Schlemmer HP, Götz M. In Vivo Repeatability and Multiscanner Reproducibility of MRI Radiomics Features in Patients With Monoclonal Plasma Cell Disorders: A Prospective Bi-institutional Study. Invest Radiol 2022. [PMID: 36165988 DOI: 10.1097/RLI.0000000000000927] [Reference Citation Analysis]
3 Cui Y, Yin F. Impact of image quality on radiomics applications. Phys Med Biol 2022;67:15TR03. [DOI: 10.1088/1361-6560/ac7fd7] [Reference Citation Analysis]