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A novel deep learning model for breast lesion classification using ultrasound Images: A multicenter data evaluation.
Sirjani, Nasim; Ghelich Oghli, Mostafa; Kazem Tarzamni, Mohammad; Gity, Masoumeh; Shabanzadeh, Ali; Ghaderi, Payam; Shiri, Isaac; Akhavan, Ardavan; Faraji, Mehri; Taghipour, Mostafa.
Afiliação
  • Sirjani N; Research and Development Department, Med Fanavaran Plus Co., Karaj, Iran.
  • Ghelich Oghli M; Research and Development Department, Med Fanavaran Plus Co., Karaj, Iran. Electronic address: m.g31_mesu@yahoo.com.
  • Kazem Tarzamni M; Department of Radiology, Imam Reza Hospital, Tabriz University of Medical Sciences, Tabriz, Iran.
  • Gity M; Department of Radiology, Advanced Diagnostic and Interventional Radiology Research Center (ADIR), Medical Imaging Center, Imam Khomeini Complex Hospital, Tehran, Iran.
  • Shabanzadeh A; Research and Development Department, Med Fanavaran Plus Co., Karaj, Iran.
  • Ghaderi P; Besat Hospital, Kurdistan University of Medical Sciences, Sanandaj, Iran.
  • Shiri I; Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva 4, Switzerland.
  • Akhavan A; Research and Development Department, Med Fanavaran Plus Co., Karaj, Iran.
  • Faraji M; Research and Development Department, Med Fanavaran Plus Co., Karaj, Iran.
  • Taghipour M; Research and Development Department, Med Fanavaran Plus Co., Karaj, Iran.
Phys Med ; 107: 102560, 2023 Mar.
Article em En | MEDLINE | ID: mdl-36878133
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Aprendizado Profundo Tipo de estudo: Clinical_trials / Prognostic_studies / Screening_studies Limite: Female / Humans Idioma: En Revista: Phys Med Assunto da revista: BIOFISICA / BIOLOGIA / MEDICINA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Irã
Texto completo
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XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Aprendizado Profundo Tipo de estudo: Clinical_trials / Prognostic_studies / Screening_studies Limite: Female / Humans Idioma: En Revista: Phys Med Assunto da revista: BIOFISICA / BIOLOGIA / MEDICINA Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Irã