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For: Song L, Lu H, Yin J. Preliminary study on discriminating HER2 2+ amplification status of breast cancers based on texture features semi-automatically derived from pre-, post-contrast, and subtraction images of DCE-MRI. PLoS One 2020;15:e0234800. [PMID: 32555662 DOI: 10.1371/journal.pone.0234800] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
Number Citing Articles
1 Feng S, Yin J. Radiomics of dynamic contrast-enhanced magnetic resonance imaging parametric maps and apparent diffusion coefficient maps to predict Ki-67 status in breast cancer. Front Oncol 2022;12. [DOI: 10.3389/fonc.2022.847880] [Reference Citation Analysis]
2 Szep M, Pintican R, Boca B, Perja A, Duma M, Feier D, Fetica B, Eniu D, Dudea SM, Chiorean A. Multiparametric MRI Features of Breast Cancer Molecular Subtypes. Medicina (Kaunas) 2022;58. [PMID: 36556918 DOI: 10.3390/medicina58121716] [Reference Citation Analysis]
3 Altabella L, Benetti G, Camera L, Cardano G, Montemezzi S, Cavedon C. Machine learning for multi-parametric breast MRI: radiomics-based approaches for lesion classification. Phys Med Biol 2022;67:15TR01. [DOI: 10.1088/1361-6560/ac7d8f] [Reference Citation Analysis]
4 Xu A, Chu X, Zhang S, Zheng J, Shi D, Lv S, Li F, Weng X. Prediction Breast Molecular Typing of Invasive Ductal Carcinoma Based on Dynamic Contrast Enhancement Magnetic Resonance Imaging Radiomics Characteristics: A Feasibility Study. Front Oncol 2022;12:799232. [DOI: 10.3389/fonc.2022.799232] [Reference Citation Analysis]
5 Cho N. Imaging features of breast cancer molecular subtypes: state of the art. J Pathol Transl Med 2021;55:16-25. [PMID: 33153242 DOI: 10.4132/jptm.2020.09.03] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]