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Decoding the molecular subtypes of breast cancer seen on multimodal ultrasound images using an assembled convolutional neural network model: A prospective and multicentre study.
Zhou, Bo-Yang; Wang, Li-Fan; Yin, Hao-Hao; Wu, Ting-Fan; Ren, Tian-Tian; Peng, Chuan; Li, De-Xuan; Shi, Hui; Sun, Li-Ping; Zhao, Chong-Ke; Xu, Hui-Xiong.
Afiliação
  • Zhou BY; Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China; Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine,
  • Wang LF; Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China; Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine,
  • Yin HH; Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China; Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine,
  • Wu TF; Translational Medicine Team, GE Healthcare, Shanghai, China.
  • Ren TT; Department of Medical Ultrasound, Ma'anshan People's Hospital, Ma'anshan, China.
  • Peng C; Department of Medical Ultrasound, Sun Yat-Sen University Cancer Center, Guangzhou, China.
  • Li DX; Beijing XiaoBaiShiJi Network Technical Co., Ltd, Beijing, China.
  • Shi H; Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China; Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine,
  • Sun LP; Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China; Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine,
  • Zhao CK; Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China; Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine,
  • Xu HX; Department of Medical Ultrasound, Center of Minimally Invasive Treatment for Tumor, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China; Ultrasound Research and Education Institute, Clinical Research Center for Interventional Medicine, School of Medicine,
EBioMedicine ; 74: 103684, 2021 Dec.
Article em En | MEDLINE | ID: mdl-34773890
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Biomarcadores Tumorais Tipo de estudo: Clinical_trials / Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Aged / Aged80 / Female / Humans / Middle aged País/Região como assunto: Asia Idioma: En Revista: EBioMedicine Ano de publicação: 2021 Tipo de documento: Article
Texto completo
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Biomarcadores Tumorais Tipo de estudo: Clinical_trials / Diagnostic_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Aged / Aged80 / Female / Humans / Middle aged País/Região como assunto: Asia Idioma: En Revista: EBioMedicine Ano de publicação: 2021 Tipo de documento: Article