Expected value of artificial intelligence in gastrointestinal endoscopy: European Society of Gastrointestinal Endoscopy (ESGE) Position Statement
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- Helmut Messmann
- III Medizinische Klinik, Universitatsklinikum Augsburg, Augsburg, Germany
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- Raf Bisschops
- Department of Gastroenterology and Hepatology, Catholic University of Leuven (KUL), TARGID, University Hospital Leuven, Leuven, Belgium
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- Giulio Antonelli
- Gastroenterology and Digestive Endoscopy Unit, Ospedale dei Castelli Hospital, Ariccia, Rome, Italy
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- Diogo Libânio
- Department of Gastroenterology, Porto Comprehensive Cancer Center, and RISE@CI-IPOP (Health Research Network), Porto, Portugal
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- Pieter Sinonquel
- Department of Gastroenterology and Hepatology, Catholic University of Leuven (KUL), TARGID, University Hospital Leuven, Leuven, Belgium
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- Mohamed Abdelrahim
- Endoscopy Department, Portsmouth Hospitals University NHS Trust, Portsmouth, UK
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- Omer F. Ahmad
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London Hospital, London, UK
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- Miguel Areia
- Gastroenterology Department, Portuguese Oncology Institute of Coimbra, Coimbra, Portugal
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- Jacques J. G. H. M. Bergman
- Department of Gastroenterology and Hepatology, Amsterdam UMC, Amsterdam, The Netherlands
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- Pradeep Bhandari
- Endoscopy Department, Portsmouth Hospitals University NHS Trust, Portsmouth, UK
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- Ivo Boskoski
- Digestive Endoscopy Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
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- Evelien Dekker
- Department of Gastroenterology and Hepatology, Amsterdam UMC, Amsterdam, The Netherlands
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- Dirk Domagk
- Department of Medicine I, Josephs-Hospital Warendorf, Academic Teaching Hospital, University of Muenster, Warendorf, Germany
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- Alanna Ebigbo
- III Medizinische Klinik, Universitatsklinikum Augsburg, Augsburg, Germany
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- Tom Eelbode
- Department of Electrical Engineering (ESAT/PSI), Medical Imaging Research Center, KU Leuven, Leuven, Belgium
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- Rami Eliakim
- Department of Gastroenterology, Sheba Medical Center Tel Hashomer & Sackler School of Medicine, Tel-Aviv University, Ramat Gan, Israel
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- Michael Häfner
- 2nd Medical Department, Barmherzige Schwestern Krankenhaus, Vienna, Austria
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- Rehan J. Haidry
- Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London Hospital, London, UK
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- Rodrigo Jover
- Servicio de Gastroenterología, Hospital General Universitario Dr. Balmis, Instituto de Investigación Biomédica de Alicante ISABIAL, Departamento de Medicina Clínica, Universidad Miguel Hernández, Alicante, Spain
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- Michal F. Kaminski
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway
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- Roman Kuvaev
- Endoscopy Department, Yaroslavl Regional Cancer Hospital, Yaroslavl, Russian Federation
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- Yuichi Mori
- Clinical Effectiveness Research Group, University of Oslo, Oslo, Norway
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- Maxime Palazzo
- European Hospital, Marseille, France
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- Alessandro Repici
- Department of Biomedical Sciences, Humanitas University, Rozzano, Milan, Italy
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- Emanuele Rondonotti
- Gastroenterology Unit, Valduce Hospital, Como, Italy
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- Matthew D. Rutter
- North Tees and Hartlepool NHS Foundation Trust, Stockton-on-Tees, UK
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- Yutaka Saito
- Endoscopy Division, National Cancer Center Hospital, Tokyo, Japan
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- Prateek Sharma
- Gastroenterology and Hepatology Division, University of Kansas School of Medicine, Kansas, USA
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- Cristiano Spada
- Digestive Endoscopy Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
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- Marco Spadaccini
- Department of Biomedical Sciences, Humanitas University, Rozzano, Milan, Italy
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- Andrew Veitch
- Department of Gastroenterology, Royal Wolverhampton Hospitals NHS Trust, Wolverhampton, UK
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- Ian M. Gralnek
- Ellen and Pinchas Mamber Institute of Gastroenterology and Hepatology, Emek Medical Center, Afula, Israel
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- Cesare Hassan
- Department of Biomedical Sciences, Humanitas University, Rozzano, Milan, Italy
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- Mario Dinis-Ribeiro
- Department of Gastroenterology, Porto Comprehensive Cancer Center, and RISE@CI-IPOP (Health Research Network), Porto, Portugal
Description
<jats:title>Abstract</jats:title><jats:p>This ESGE Position Statement defines the expected value of artificial intelligence (AI) for the diagnosis and management of gastrointestinal neoplasia within the framework of the performance measures already defined by ESGE. This is based on the clinical relevance of the expected task and the preliminary evidence regarding artificial intelligence in artificial or clinical settings.</jats:p><jats:p> Main recommendations: (1) For acceptance of AI in assessment of completeness of upper GI endoscopy, the adequate level of mucosal inspection with AI should be comparable to that assessed by experienced endoscopists. (2) For acceptance of AI in assessment of completeness of upper GI endoscopy, automated recognition and photodocumentation of relevant anatomical landmarks should be obtained in ≥90% of the procedures. (3) For acceptance of AI in the detection of Barrett’s high grade intraepithelial neoplasia or cancer, the AI-assisted detection rate for suspicious lesions for targeted biopsies should be comparable to that of experienced endoscopists with or without advanced imaging techniques. (4) For acceptance of AI in the management of Barrett’s neoplasia, AI-assisted selection of lesions amenable to endoscopic resection should be comparable to that of experienced endoscopists. (5) For acceptance of AI in the diagnosis of gastric precancerous conditions, AI-assisted diagnosis of atrophy and intestinal metaplasia should be comparable to that provided by the established biopsy protocol, including the estimation of extent, and consequent allocation to the correct endoscopic surveillance interval. (6) For acceptance of artificial intelligence for automated lesion detection in small-bowel capsule endoscopy (SBCE), the performance of AI-assisted reading should be comparable to that of experienced endoscopists for lesion detection, without increasing but possibly reducing the reading time of the operator. (7) For acceptance of AI in the detection of colorectal polyps, the AI-assisted adenoma detection rate should be comparable to that of experienced endoscopists. (8) For acceptance of AI optical diagnosis (computer-aided diagnosis [CADx]) of diminutive polyps (≤5 mm), AI-assisted characterization should match performance standards for implementing resect-and-discard and diagnose-and-leave strategies. (9) For acceptance of AI in the management of polyps ≥ 6 mm, AI-assisted characterization should be comparable to that of experienced endoscopists in selecting lesions amenable to endoscopic resection.</jats:p>
Journal
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- Endoscopy
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Endoscopy 54 (12), 1211-1231, 2022-10-21
Georg Thieme Verlag KG
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Details 詳細情報について
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- CRID
- 1360580232185999872
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- ISSN
- 14388812
- 0013726X
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- Data Source
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- Crossref
- KAKEN