Artificial intelligence in GI endoscopy: stumbling blocks, gold standards and the role of endoscopy societies
Gut
.
2022 Mar;71(3):451-454.
doi: 10.1136/gutjnl-2020-323115.
Epub 2021 Jan 21.
Authors
Rüdiger Schmitz
1
2
3
,
Rene Werner
2
3
,
Alessandro Repici
4
5
,
Raf Bisschops
6
,
Alexander Meining
7
,
Michael Zornow
8
,
Helmut Messmann
9
,
Cesare Hassan
10
,
Prateek Sharma
11
,
Thomas Rösch
12
Affiliations
1
Interdisciplinary Endoscopy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
2
Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
3
Center for Biomedical Artificial Intelligence (bAIome), University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
4
Humanitas Clinical and Research Center - IRCCS, Rozzano, Italy.
5
Humanitas University, Department of Biomedical Sciences, Milan, Italy.
6
Gastroenterology, University Hospital Gasthuisberg, Leuven, Belgium.
7
Department of Gastroenterology, University of Würzburg, Würzburg, Germany.
8
Chair for Public and European Law, University of Göttingen, Göttingen, Germany.
9
Department of Gastroenterology, Universitätsklinikum Augsburg, Augsburg, Germany.
10
Gastroenterology Unit, Nuovo Regina Margherita Hospital, Rome, Italy.
11
Division of Gastroenterology and Hepatology, Veterans Affairs Medical Center and University of Kansas, Lawrence, Kansas, USA.
12
Interdisciplinary Endoscopy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany t.roesch@uke.de.
PMID:
33479051
DOI:
10.1136/gutjnl-2020-323115
No abstract available
Keywords:
computerised image analysis; endoscopy.
MeSH terms
Artificial Intelligence*
Endoscopy, Gastrointestinal*
Humans