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Axillary lymph node metastasis prediction by contrast-enhanced computed tomography images for breast cancer patients based on deep learning.
Liu, Ziyi; Ni, Sijie; Yang, Chunmei; Sun, Weihao; Huang, Deqing; Su, Hu; Shu, Jian; Qin, Na.
Afiliación
  • Liu Z; Institute of Systems Science and Technology, School of Electrical Engineering, Southwest Jiaotong University, Chengdu, 611756, China.
  • Ni S; Institute of Systems Science and Technology, School of Electrical Engineering, Southwest Jiaotong University, Chengdu, 611756, China.
  • Yang C; Department of Radiology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China.
  • Sun W; Institute of Systems Science and Technology, School of Electrical Engineering, Southwest Jiaotong University, Chengdu, 611756, China.
  • Huang D; Institute of Systems Science and Technology, School of Electrical Engineering, Southwest Jiaotong University, Chengdu, 611756, China.
  • Su H; Institute of Systems Science and Technology, School of Electrical Engineering, Southwest Jiaotong University, Chengdu, 611756, China.
  • Shu J; Department of Radiology, The Affiliated Hospital of Southwest Medical University, Luzhou, 646000, China. Electronic address: shujiannc@163.com.
  • Qin N; Institute of Systems Science and Technology, School of Electrical Engineering, Southwest Jiaotong University, Chengdu, 611756, China. Electronic address: qinna@swjtu.edu.cn.
Comput Biol Med ; 136: 104715, 2021 09.
Article en En | MEDLINE | ID: mdl-34388460
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Aprendizaje Profundo Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: Comput Biol Med Año: 2021 Tipo del documento: Article País de afiliación: China
Texto completo
Imprimir
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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Aprendizaje Profundo Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: Comput Biol Med Año: 2021 Tipo del documento: Article País de afiliación: China