Artificial intelligence identifies and quantifies colonoscopy blind spots.

Autor: 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.; Department of Computer Science, 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 Radiation Oncology, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA., Pizer S; Department of Computer Science, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
Jazyk: angličtina
Zdroj: Endoscopy [Endoscopy] 2021 Dec; Vol. 53 (12), pp. 1284-1286. Date of Electronic Publication: 2021 Feb 04.
DOI: 10.1055/a-1346-7455
Abstrakt: Competing Interests: All authors are patent holders. Sarah K. McGill and Julian Rosenman have received research funding from Olympus.
Databáze: MEDLINE