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AI-based improvement in lung cancer detection on chest radiographs: results of a multi-reader study in NLST dataset.
Yoo, Hyunsuk; Lee, Sang Hyup; Arru, Chiara Daniela; Doda Khera, Ruhani; Singh, Ramandeep; Siebert, Sean; Kim, Dohoon; Lee, Yuna; Park, Ju Hyun; Eom, Hye Joung; Digumarthy, Subba R; Kalra, Mannudeep K.
Afiliação
  • Yoo H; Lunit, Seoul, Korea.
  • Lee SH; Lunit, Seoul, Korea.
  • Arru CD; Division of Thoracic Imaging, Department of Radiology, Massachusetts General Hospital, 75 Blossom Court, Boston, MA, 02114, USA.
  • Doda Khera R; Harvard Medical School, Boston, MA, USA.
  • Singh R; Division of Thoracic Imaging, Department of Radiology, Massachusetts General Hospital, 75 Blossom Court, Boston, MA, 02114, USA.
  • Siebert S; Harvard Medical School, Boston, MA, USA.
  • Kim D; Division of Thoracic Imaging, Department of Radiology, Massachusetts General Hospital, 75 Blossom Court, Boston, MA, 02114, USA.
  • Lee Y; Harvard Medical School, Boston, MA, USA.
  • Park JH; Division of Thoracic Imaging, Department of Radiology, Massachusetts General Hospital, 75 Blossom Court, Boston, MA, 02114, USA.
  • Eom HJ; Harvard Medical School, Boston, MA, USA.
  • Digumarthy SR; Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.
  • Kalra MK; Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.
Eur Radiol ; 31(12): 9664-9674, 2021 Dec.
Article em En | MEDLINE | ID: mdl-34089072
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Neoplasias Pulmonares Tipo de estudo: Diagnostic_studies / Screening_studies Limite: Humans Idioma: En Revista: Eur Radiol Assunto da revista: RADIOLOGIA Ano de publicação: 2021 Tipo de documento: Article
Texto completo
Adicionar na Minha BVS
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Neoplasias Pulmonares Tipo de estudo: Diagnostic_studies / Screening_studies Limite: Humans Idioma: En Revista: Eur Radiol Assunto da revista: RADIOLOGIA Ano de publicação: 2021 Tipo de documento: Article