Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: A machine learning, multicenter study

Yu, Yunfang; He, Zifan; Ouyang, Jie; Tan, Yujie; Chen, Yongjian; Gu, Yang; Mao, Luhui; Ren, Wei; Wang, Jue; Lin, Lili; Wu, Zhuo; Liu, Jingwen; Ou, Qiyun; Hu, Qiugen; Li, Anlin; Chen, Kai; Li, Chenchen; Lu, Nian; Li, Xiaohong; Su, Fengxi; Liu, Qiang; Xie, Chuanmiao; Yao, Herui

doi:10.1016/j.ebiom.2021.103460

Public

Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: A machine learning, multicenter study

Published in EBioMedicine • Jul 1, 2021

Authors:

Yunfang Yu

Zifan He

Jie Ouyang

Abstract

BACKGROUND: in current clinical practice, the standard evaluation for axillary lymph node (ALN) status in breast cancer has a low efficiency and is based on an invasive procedure that causes operative-associated complications in many patients. Therefore, we aimed to use machine learning techniques t...

Subject

Medicine

Radiomics

Magnetic resonance imaging

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