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Cited by in F6Publishing
For: Nougaret S, Tibermacine H, Tardieu M, Sala E. Radiomics: an Introductory Guide to What It May Foretell.Curr Oncol Rep. 2019;21:70. [PMID: 31240403 DOI: 10.1007/s11912-019-0815-1] [Cited by in Crossref: 9] [Cited by in F6Publishing: 10] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 Tu SJ, Chen WY, Wu CT. Uncertainty measurement of radiomics features against inherent quantum noise in computed tomography imaging. Eur Radiol 2021. [PMID: 33852047 DOI: 10.1007/s00330-021-07943-5] [Reference Citation Analysis]
2 Yang S, Wu N, Zhang L, Li M. Evaluation of the linear interpolation method in correcting the influence of slice thicknesses on radiomic feature values in solid pulmonary nodules: a prospective patient study. Ann Transl Med 2021;9:279. [PMID: 33708906 DOI: 10.21037/atm-20-2992] [Reference Citation Analysis]
3 Gutmann DAP, Rospleszcz S, Rathmann W, Schlett CL, Peters A, Wachinger C, Gatidis S, Bamberg F. MRI-Derived Radiomics Features of Hepatic Fat Predict Metabolic States in Individuals without Cardiovascular Disease. Acad Radiol 2021;28 Suppl 1:S1-S10. [PMID: 32800693 DOI: 10.1016/j.acra.2020.06.030] [Cited by in Crossref: 3] [Cited by in F6Publishing: 5] [Article Influence: 3.0] [Reference Citation Analysis]
4 Petresc B, Lebovici A, Caraiani C, Feier DS, Graur F, Buruian MM. Pre-Treatment T2-WI Based Radiomics Features for Prediction of Locally Advanced Rectal Cancer Non-Response to Neoadjuvant Chemoradiotherapy: A Preliminary Study. Cancers (Basel) 2020;12:E1894. [PMID: 32674345 DOI: 10.3390/cancers12071894] [Cited by in Crossref: 6] [Cited by in F6Publishing: 5] [Article Influence: 3.0] [Reference Citation Analysis]
5 Deng X, Liu M, Sun J, Li M, Liu D, Li L, Fang J, Wang X, Zhang J. Feasibility of MRI-based radiomics features for predicting lymph node metastases and VEGF expression in cervical cancer. Eur J Radiol 2021;134:109429. [PMID: 33290975 DOI: 10.1016/j.ejrad.2020.109429] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
6 Li B, Sun M, Yao P, Chang Z, Liu Z. Radiogenomics: A Valuable Tool for the Clinical Assessment and Research of Ovarian Cancer. J Comput Assist Tomogr 2022;46:371-8. [DOI: 10.1097/rct.0000000000001279] [Reference Citation Analysis]
7 Yin R, Jiang M, Lv WZ, Jiang F, Li J, Hu B, Cui XW, Dietrich CF. Study Processes and Applications of Ultrasomics in Precision Medicine. Front Oncol 2020;10:1736. [PMID: 33014858 DOI: 10.3389/fonc.2020.01736] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
8 Lewis S, Hectors S, Taouli B. Radiomics of hepatocellular carcinoma. Abdom Radiol (NY) 2021;46:111-23. [PMID: 31925492 DOI: 10.1007/s00261-019-02378-5] [Cited by in Crossref: 21] [Cited by in F6Publishing: 19] [Article Influence: 21.0] [Reference Citation Analysis]
9 Nougaret S, McCague C, Tibermacine H, Vargas HA, Rizzo S, Sala E. Radiomics and radiogenomics in ovarian cancer: a literature review. Abdom Radiol (NY) 2021;46:2308-22. [PMID: 33174120 DOI: 10.1007/s00261-020-02820-z] [Cited by in Crossref: 12] [Cited by in F6Publishing: 7] [Article Influence: 12.0] [Reference Citation Analysis]
10 Chiappa V, Interlenghi M, Salvatore C, Bertolina F, Bogani G, Ditto A, Martinelli F, Castiglioni I, Raspagliesi F. Using rADioMIcs and machine learning with ultrasonography for the differential diagnosis of myometRiAL tumors (the ADMIRAL pilot study). Radiomics and differential diagnosis of myometrial tumors. Gynecol Oncol 2021;161:838-44. [PMID: 33867144 DOI: 10.1016/j.ygyno.2021.04.004] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
11 Stanzione A, Verde F, Romeo V, Boccadifuoco F, Mainenti PP, Maurea S. Radiomics and machine learning applications in rectal cancer: Current update and future perspectives. World J Gastroenterol 2021; 27(32): 5306-5321 [PMID: 34539134 DOI: 10.3748/wjg.v27.i32.5306] [Reference Citation Analysis]
12 Davey MS, Davey MG, Ryan ÉJ, Hogan AM, Kerin MJ, Joyce M. The use of radiomic analysis of magnetic resonance imaging in predicting distant metastases of rectal carcinoma following surgical resection: A systematic review and meta-analysis. Colorectal Dis 2021. [PMID: 34536962 DOI: 10.1111/codi.15919] [Reference Citation Analysis]