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Deep learning with convolutional neural network in the assessment of breast cancer molecular subtypes based on US images: a multicenter retrospective study.
Jiang, Meng; Zhang, Di; Tang, Shi-Chu; Luo, Xiao-Mao; Chuan, Zhi-Rui; Lv, Wen-Zhi; Jiang, Fan; Ni, Xue-Jun; Cui, Xin-Wu; Dietrich, Christoph F.
Afiliação
  • Jiang M; Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jiefang Avenue, Wuhan, 430030, Hubei Province, China.
  • Zhang D; Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Nantong, China.
  • Tang SC; Department of Medical Ultrasound, Hunan Cancer Hospital/The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, 410013, Hunan, China.
  • Luo XM; Department of Medical Ultrasound, Yunnan Cancer Hospital & The Third Affiliated Hospital of Kunming Medical University, Kunming, 650118, China.
  • Chuan ZR; Department of Medical Ultrasound, Yunnan Cancer Hospital & The Third Affiliated Hospital of Kunming Medical University, Kunming, 650118, China.
  • Lv WZ; Department of Artificial Intelligence, Julei Technology Company, Wuhan, 430030, China.
  • Jiang F; Department of Ultrasound, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
  • Ni XJ; Department of Medical Ultrasound, Affiliated Hospital of Nantong University, Nantong, China.
  • Cui XW; Department of Medical Ultrasound, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jiefang Avenue, Wuhan, 430030, Hubei Province, China. cuixinwu@live.cn.
  • Dietrich CF; Department of Internal Medicine, Hirslanden Clinic, Schänzlihalde 11, 3013, Bern, Switzerland.
Eur Radiol ; 31(6): 3673-3682, 2021 Jun.
Article em En | MEDLINE | ID: mdl-33226454
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Observational_studies / Prognostic_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article