Invasive ductal breast cancer molecular subtype prediction by MRI radiomic and clinical features based on machine learning.

Sheng, Weiyong; Xia, Shouli; Wang, Yaru; Yan, Lizhao; Ke, Songqing; Mellisa, Evelyn; Gong, Fen; Zheng, Yun; Tang, Tiansheng

Sheng, Weiyong; Xia, Shouli; Wang, Yaru; Yan, Lizhao; Ke, Songqing; Mellisa, Evelyn; Gong, Fen; Zheng, Yun; Tang, Tiansheng.

Afiliação

Sheng W; Department of Cardiothoracic Surgery, The First Affiliated Hospital of Wannan Medical College, Wuhu, China.
Xia S; First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China.
Wang Y; First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China.
Yan L; Department of Hand Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Ke S; Department of Science and Technology Research Management, Wuhan Blood Center, Wuhan, China.
Mellisa E; Department of Emergency Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Gong F; First Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou, China.
Zheng Y; Department of Radiology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Tang T; Department of Cardiothoracic Surgery, The First Affiliated Hospital of Wannan Medical College, Wuhu, China.

Front Oncol ; 12: 964605, 2022.

Article em En | MEDLINE | ID: mdl-36172153

Palavras-chave

MRI; breast cancer; machine learning; molecular subtypes; radiomics; three-dimension

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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