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Proceedings from the First Global Artificial Intelligence in Gastroenterology and Endoscopy Summit.
Parasa, Sravanthi; Wallace, Michael; Bagci, Ulas; Antonino, Mark; Berzin, Tyler; Byrne, Michael; Celik, Haydar; Farahani, Keyvan; Golding, Martin; Gross, Seth; Jamali, Vafa; Mendonca, Paulo; Mori, Yuichi; Ninh, Andrew; Repici, Alessandro; Rex, Douglas; Skrinak, Kris; Thakkar, Shyam J; van Hooft, Jeanin E; Vargo, John; Yu, Honggang; Xu, Ziyue; Sharma, Prateek.
Afiliación
  • Parasa S; Department of Gastroenterology, Swedish Medical Center, Seattle, Washington, USA.
  • Wallace M; Department of Medicine, Mayo Clinic, Director, Digestive Diseases Research Program, Editor in Chief Gastrointestinal Endoscopy, President, Florida Gastroenterology Society, Jacksonville, Florida, USA.
  • Bagci U; Artificial Intelligence in Medicine (AIM), Center for Research in Computer Vision, University of Central Florida, Orlando, Florida, USA.
  • Antonino M; Gastroenterology and Endoscopy Devices Team, Division of Renal, Gastrointestinal, Obesity and Transplant Devices, Office of Gastrorenal, ObGyn, General Hospital and Urology Devices, Office of Product Evaluation and Quality, Center for Devices and Radiological Health, U.S. Food and Drug Administratio
  • Berzin T; Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
  • Byrne M; Division of Gastroenterology, Vancouver General Hospital/University of British Columbia, Vancouver, British Columbia, Canada.
  • Celik H; Clinical Center, National Institutes of Health, Bethesda, Maryland, USA; George Washington University, Washington, DC, USA.
  • Farahani K; Image-Guided Interventions and Imaging Informatics, National Cancer Institute, National Institutes of Health, Rockville, Maryland, USA.
  • Golding M; Gastroenterology and Endoscopy Devices Team, Division of Renal, Gastrointestinal, Obesity and Transplant Devices, Office of Gastrorenal, ObGyn, General Hospital and Urology Devices, Office of Product Evaluation and Quality, Center for Devices and Radiological Health, U.S. Food and Drug Administratio
  • Gross S; Department of Medicine, Division of Gastroenterology, Clinical Care and Quality, NYU Langone Health, New York, New York, USA.
  • Jamali V; Respiratory, Gastrointestinal & Informatics, Medtronic Inc, Boulder, Colorado, USA.
  • Mendonca P; Digestive Disease Center, Showa University, Northern Yokohama Hospital, Yokohama, Japan.
  • Mori Y; University of Tokyo, Tokyo, Japan.
  • Ninh A; Docbot, Irvine, California, USA.
  • Repici A; Digestive Endoscopy Unit, Humanitas, Research Hospital, Milan, Italy.
  • Rex D; Departments of Medicine, Endoscopy, and Gastroenterology, Indiana University of School of Medicine, Indianapolis, Indiana, USA.
  • Skrinak K; Global Machine Learning Segment Lead, Amazon Web Services, New York, New York, USA.
  • Thakkar SJ; Department of Endoscopy, Allegheny Health Network, Department of Medicine, Temple University, Philadelphia, Pennsylvania, USA; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA.
  • van Hooft JE; Gastrointestinal Oncology Centre Amsterdam, Amsterdam, The Netherlands.
  • Vargo J; Department of Medicine, Gastroenterology, Hepatology & Nutrition, Cleveland Clinic, Cleveland, Ohio, USA.
  • Yu H; Division of Gastroenterology, Renmin Hospital, Wuhan University, Wuhan, China.
  • Xu Z; Medical Image Analysis, NVIDIA, Bethesda, Maryland, USA.
  • Sharma P; Division of Gastroenterology and Hepatology, University of Kansas School of Medicine, Kansas City, Kansas, USA.
Gastrointest Endosc ; 92(4): 938-945.e1, 2020 10.
Article en En | MEDLINE | ID: mdl-32343978
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Gastroenterología Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies Límite: Humans Idioma: En Revista: Gastrointest Endosc Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Gastroenterología Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies Límite: Humans Idioma: En Revista: Gastrointest Endosc Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos