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Multi-label annotation of text reports from computed tomography of the chest, abdomen, and pelvis using deep learning.
D'Anniballe, Vincent M; Tushar, Fakrul Islam; Faryna, Khrystyna; Han, Songyue; Mazurowski, Maciej A; Rubin, Geoffrey D; Lo, Joseph Y.
Afiliação
  • D'Anniballe VM; Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, 2424 Erwin Rd. Ste. 302, Durham, NC, 27705, USA.
  • Tushar FI; Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, 2424 Erwin Rd. Ste. 302, Durham, NC, 27705, USA.
  • Faryna K; Department of Electrical and Computer Engineering, Pratt School of Engineering, Duke University, Durham, NC, USA.
  • Han S; Erasmus+ Joint Master in Medical Imaging and Applications, University of Girona, Girona, Spain.
  • Mazurowski MA; Erasmus+ Joint Master in Medical Imaging and Applications, University of Girona, Girona, Spain.
  • Rubin GD; School of Software Engineering, South China University of Technology, Guangzhou, Guangdong, China.
  • Lo JY; Center for Virtual Imaging Trials, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, 2424 Erwin Rd. Ste. 302, Durham, NC, 27705, USA.
BMC Med Inform Decis Mak ; 22(1): 102, 2022 04 15.
Article em En | MEDLINE | ID: mdl-35428335
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Tipo de estudo: Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aprendizado Profundo Tipo de estudo: Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2022 Tipo de documento: Article