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Application of artificial intelligence using a novel EUS-based convolutional neural network model to identify and distinguish benign and malignant hepatic masses.
Marya, Neil B; Powers, Patrick D; Fujii-Lau, Larissa; Abu Dayyeh, Barham K; Gleeson, Ferga C; Chen, Shigao; Long, Zaiyang; Hough, David M; Chandrasekhara, Vinay; Iyer, Prasad G; Rajan, Elizabeth; Sanchez, William; Sawas, Tarek; Storm, Andrew C; Wang, Kenneth K; Levy, Michael J.
Afiliación
  • Marya NB; Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.
  • Powers PD; Independent Researcher, Chelsea, Massachusetts.
  • Fujii-Lau L; Department of Gastroenterology, The Queen's Medical Center, Honolulu, Hawaii.
  • Abu Dayyeh BK; Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.
  • Gleeson FC; Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.
  • Chen S; Division of Diagnostic Radiology, Mayo Clinic, Rochester, Minnesota, USA.
  • Long Z; Division of Diagnostic Radiology, Mayo Clinic, Rochester, Minnesota, USA.
  • Hough DM; Division of Diagnostic Radiology, Mayo Clinic, Rochester, Minnesota, USA.
  • Chandrasekhara V; Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.
  • Iyer PG; Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.
  • Rajan E; Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.
  • Sanchez W; Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.
  • Sawas T; Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.
  • Storm AC; Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.
  • Wang KK; Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.
  • Levy MJ; Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota.
Gastrointest Endosc ; 93(5): 1121-1130.e1, 2021 05.
Article en En | MEDLINE | ID: mdl-32861752
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Neoplasias Hepáticas Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies Límite: Humans Idioma: En Revista: Gastrointest Endosc Año: 2021 Tipo del documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Inteligencia Artificial / Neoplasias Hepáticas Tipo de estudio: Diagnostic_studies / Observational_studies / Prognostic_studies Límite: Humans Idioma: En Revista: Gastrointest Endosc Año: 2021 Tipo del documento: Article