Prediction of sentinel lymph node metastasis in breast cancer using multiparametric MRI radiomics and machine learning models
|更新时间:2025-12-15
|
Prediction of sentinel lymph node metastasis in breast cancer using multiparametric MRI radiomics and machine learning models
“The latest research shows that the combination of multi parameter MRI and machine learning model can effectively predict sentinel lymph node metastasis of breast cancer.”
Ma’anshan City Science and Technology Program(YL-2023-4);Anhui Medical University Young Scientist Fund(2023xkj122);Ma’anshan City Health and Wellness Science and Technology Key Research Project(MASWJ2022a001)
Hongkai YANG, Xuan QI, Wuling WANG, et al. Prediction of sentinel lymph node metastasis in breast cancer using multiparametric MRI radiomics and machine learning models[J]. Oncoradiology, 2025, 34(2): 172-182.
DOI:
Hongkai YANG, Xuan QI, Wuling WANG, et al. Prediction of sentinel lymph node metastasis in breast cancer using multiparametric MRI radiomics and machine learning models[J]. Oncoradiology, 2025, 34(2): 172-182. DOI: 10.19732/j.cnki.2096-6210.2025.02.009.
Prediction of sentinel lymph node metastasis in breast cancer using multiparametric MRI radiomics and machine learning models
The value of radiomics features derived from the T2WI-FS assisted preoperative prediction of axillary lymph node metastasis of breast cancer
Radiomics in Breast Cancer
Observer consistency study based on dynamic enhanced MRI radiomics parameters
MRI radiomics in breast cancer
Prediction of lymphovascular invasion using multiparametric MRI habitat radiomics based on machine learning algorithms in gastric cancer
Related Author
WANG Meng
LIU Zhou
WEN Jie
HE Cuiju
GENG Yayuan
LUO Dehong
XIE Tianwen
PENG Weijun
Related Institution
Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
Huiying Medical Technology Beijing Co., Ltd
Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College
Department of Information Management, Shanxi Province Cancer Hospital /Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences /Cancer Hospital Affiliated to Shanxi Medical University
Department of Imaging, Shanxi Province Cancer Hospital /Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences /Cancer Hospital Affiliated to Shanxi Medical University