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For:	He X, Zhang H, Zhang T, Han F, Song B. Predictive models composed by radiomic features extracted from multi-detector computed tomography images for predicting low- and high- grade clear cell renal cell carcinoma: A STARD-compliant article. Medicine (Baltimore) 2019;98:e13957. [PMID: 30633175 DOI: 10.1097/MD.0000000000013957] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 2.0] [Reference Citation Analysis]

For:

He X, Zhang H, Zhang T, Han F, Song B. Predictive models composed by radiomic features extracted from multi-detector computed tomography images for predicting low- and high- grade clear cell renal cell carcinoma: A STARD-compliant article. Medicine (Baltimore) 2019;98:e13957. [PMID: 30633175 DOI: 10.1097/MD.0000000000013957] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 2.0] [Reference Citation Analysis]

Number	Citing Articles
1	Moldovanu CG, Boca B, Lebovici A, Tamas-Szora A, Feier DS, Crisan N, Andras I, Buruian MM. Preoperative Predicting the WHO/ISUP Nuclear Grade of Clear Cell Renal Cell Carcinoma by Computed Tomography-Based Radiomics Features. J Pers Med 2020;11:8. [PMID: 33374569 DOI: 10.3390/jpm11010008] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
2	Yu XP, Wang L, Yu HY, Zou YW, Wang C, Jiao JW, Hong H, Zhang S. MDCT-Based Radiomics Features for the Differentiation of Serous Borderline Ovarian Tumors and Serous Malignant Ovarian Tumors. Cancer Manag Res 2021;13:329-36. [PMID: 33488120 DOI: 10.2147/CMAR.S284220] [Reference Citation Analysis]
3	Xv Y, Lv F, Guo H, Zhou X, Tan H, Xiao M, Zheng Y. Machine learning-based CT radiomics approach for predicting WHO/ISUP nuclear grade of clear cell renal cell carcinoma: an exploratory and comparative study. Insights Imaging 2021;12:170. [PMID: 34800179 DOI: 10.1186/s13244-021-01107-1] [Reference Citation Analysis]
4	Cui E, Li Z, Ma C, Li Q, Lei Y, Lan Y, Yu J, Zhou Z, Li R, Long W, Lin F. Predicting the ISUP grade of clear cell renal cell carcinoma with multiparametric MR and multiphase CT radiomics. Eur Radiol. 2020;30:2912-2921. [PMID: 32002635 DOI: 10.1007/s00330-019-06601-1] [Cited by in Crossref: 20] [Cited by in F6Publishing: 20] [Article Influence: 10.0] [Reference Citation Analysis]
5	Han D, Yu Y, Yu N, Dang S, Wu H, Jialiang R, He T. Prediction models for clear cell renal cell carcinoma ISUP/WHO grade: comparison between CT radiomics and conventional contrast-enhanced CT. Br J Radiol 2020;93:20200131. [PMID: 32706977 DOI: 10.1259/bjr.20200131] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
6	Bhandari A, Ibrahim M, Sharma C, Liong R, Gustafson S, Prior M. CT-based radiomics for differentiating renal tumours: a systematic review. Abdom Radiol (NY) 2021;46:2052-63. [PMID: 33136182 DOI: 10.1007/s00261-020-02832-9] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 1.5] [Reference Citation Analysis]