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Artificial intelligence identifies and quantifies colonoscopy blind spots.
McGill, Sarah K; Rosenman, Julian; Wang, Rui; Ma, Ruibin; Frahm, Jan-Michael; Pizer, Stephen.
  • McGill SK; Department of Internal Medicine, Division of Gastroenterology and Hepatology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
  • Rosenman J; Department of Radiation Oncology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
  • Wang R; Department of Computer Science, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
  • Ma R; Department of Computer Science, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
  • Frahm JM; Department of Computer Science, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
  • Pizer S; Department of Radiation Oncology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Endoscopy ; 53(12): 1284-1286, 2021 12.
Article en En | MEDLINE | ID: mdl-33540438
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias Colorrectales / Pólipos del Colon Límite: Humans Idioma: En Año: 2021 Tipo del documento: Article
Texto completo
Imprimir
XML
PubMed Links
Search on Google

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias Colorrectales / Pólipos del Colon Límite: Humans Idioma: En Año: 2021 Tipo del documento: Article