Prediction of Tumor Shrinkage Pattern to Neoadjuvant Chemotherapy Using a Multiparametric MRI-Based Machine Learning Model in Patients With Breast Cancer

Aim: After neoadjuvant chemotherapy (NACT), tumor shrinkage pattern is a more reasonable outcome to decide a possible breast-conserving surgery (BCS) than pathological complete response (pCR). The aim of this article was to establish a machine learning model combining radiomics features from multipa...

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Detalhes bibliográficos

Principais autores:	Yuhong Huang, Wenben Chen, Xiaoling Zhang, Shaofu He, Nan Shao, Huijuan Shi, Zhenzhe Lin, Xueting Wu, Tongkeng Li, Haotian Lin, Ying Lin
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Frontiers Media S.A. 2021-07-01
coleção:	Frontiers in Bioengineering and Biotechnology
Assuntos:	breast cancer multi-parametric MRI neoadjuvant chemotherapy radiomics machine learning tumor shrinkage pattern
Acesso em linha:	https://www.frontiersin.org/articles/10.3389/fbioe.2021.662749/full
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