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Cited by in F6Publishing
For: Pötsch N, Dietzel M, Kapetas P, Clauser P, Pinker K, Ellmann S, Uder M, Helbich T, Baltzer PAT. An A.I. classifier derived from 4D radiomics of dynamic contrast-enhanced breast MRI data: potential to avoid unnecessary breast biopsies. Eur Radiol 2021;31:5866-76. [PMID: 33744990 DOI: 10.1007/s00330-021-07787-z] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 2.0] [Reference Citation Analysis]
Number Citing Articles
1 Reig B. Radiomics and deep learning methods in expanding the use of screening breast MRI. Eur Radiol 2021;31:5863-5. [PMID: 34014381 DOI: 10.1007/s00330-021-08056-9] [Reference Citation Analysis]
2 Bitencourt A, Daimiel Naranjo I, Lo Gullo R, Rossi Saccarelli C, Pinker K. AI-enhanced breast imaging: Where are we and where are we heading? Eur J Radiol 2021;142:109882. [PMID: 34392105 DOI: 10.1016/j.ejrad.2021.109882] [Reference Citation Analysis]
3 Satake H, Ishigaki S, Ito R, Naganawa S. Radiomics in breast MRI: current progress toward clinical application in the era of artificial intelligence. Radiol Med 2021. [PMID: 34704213 DOI: 10.1007/s11547-021-01423-y] [Reference Citation Analysis]
4 Mao N, Shi Y, Lian C, Wang Z, Zhang K, Xie H, Zhang H, Chen Q, Cheng G, Xu C, Dai Y. Intratumoral and peritumoral radiomics for preoperative prediction of neoadjuvant chemotherapy effect in breast cancer based on contrast-enhanced spectral mammography. Eur Radiol. [DOI: 10.1007/s00330-021-08414-7] [Reference Citation Analysis]
5 Caballo M, Sanderink WBG, Han L, Gao Y, Athanasiou A, Mann RM. Four-Dimensional Machine Learning Radiomics for the Pretreatment Assessment of Breast Cancer Pathologic Complete Response to Neoadjuvant Chemotherapy in Dynamic Contrast-Enhanced MRI. J Magn Reson Imaging 2022. [PMID: 35633290 DOI: 10.1002/jmri.28273] [Reference Citation Analysis]