Prediction of axillary lymph node metastasis in early breast cancer patients with ultrasonic videos based deep learning.

Li, Wei-Bin; Du, Zhi-Cheng; Liu, Yue-Jie; Gao, Jun-Xue; Wang, Jia-Gang; Dai, Qian; Huang, Wen-He

Li, Wei-Bin; Du, Zhi-Cheng; Liu, Yue-Jie; Gao, Jun-Xue; Wang, Jia-Gang; Dai, Qian; Huang, Wen-He.

Afiliación

Li WB; Cancer Center and Department of Breast and Thyroid Surgery, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, China.
Du ZC; Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer, Xiamen, China.
Liu YJ; Xiamen Key Laboratory of Endocrine-Related Cancer Precision Medicine, Xiamen, China.
Gao JX; Xiamen Research Center of Clinical Medicine in Breast and Thyroid Cancers, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, China.
Wang JG; Department of Ultrasonic Medicine Affiliated Hospital of Xizang Minzu University, Xianyang, China.
Dai Q; Cancer Center and Department of Breast and Thyroid Surgery, Xiang'an Hospital, School of Medicine, Xiamen University, Xiamen, China.
Huang WH; Fujian Key Laboratory of Precision Diagnosis and Treatment in Breast Cancer, Xiamen, China.

Front Oncol ; 13: 1219838, 2023.

Article en En | MEDLINE | ID: mdl-37719009

Palabras clave

artificial intelligence; axillary lymph node metastasis; breast lesion; deep learning model; ultrasound video image

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Oncol Año: 2023 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

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