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©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. Oct 14, 2020; 26(38): 5784-5796
Published online Oct 14, 2020. doi: 10.3748/wjg.v26.i38.5784
Published online Oct 14, 2020. doi: 10.3748/wjg.v26.i38.5784
Role of artificial intelligence in the diagnosis of oesophageal neoplasia: 2020 an endoscopic odyssey
Mohamed Hussein, Laurence B Lovat, Wellcome/EPSRC Centre for Interventional and Surgical Sciences, Division of Surgery and Interventional Sciences, University College London, London W1W 7TY, United Kingdom
Juana González-Bueno Puyal, Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London, London W1W 7TY, United Kingdom and Odin Vision, London W1W 7TS, United Kingdom
Peter Mountney, Odin Vision, London W1W 7TS, United Kingdom
Rehan Haidry, Department of GI Services, University College London Hospital, London NW1 2BU, United Kingdom
Author contributions: Each author contributed to the design of the manuscript; each author was involved in the literature review, drafting, revision, editing and final approval of the final version of the manuscript.
Conflict-of-interest statement: Mohamed Hussein: No conflict of interest. Juana Gonzalez-Bueno Puyal: Employee at odin vision. Peter Mountney: Odin Vision employee. Laurence B lovat: Consultancy and minor share holder Odin Vision. Rehan Haidry: Educational grants to support research infrastructure from Medtronic ltd. Cook endoscopy (fellowship support), Pentax Europe, C2 therapeutics, Beamline diagnostic, Fractyl Ltd.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Corresponding author: Mohamed Hussein, BSc, MBBS, MRCP, Academic Fellow, Wellcome/EPSRC Centre for Interventional and Surgical Sciences, Division of Surgery and Interventional Sciences, University College London, Charles Bell House, 43-45 Foley Street, Fitzrovia, London W1W 7TY, United Kingdom. mohamed.hussein3@nhs.net
Received: May 27, 2020
Peer-review started: May 27, 2020
First decision: July 29, 2020
Revised: August 12, 2020
Accepted: September 12, 2020
Article in press: September 12, 2020
Published online: October 14, 2020
Processing time: 139 Days and 15.1 Hours
Peer-review started: May 27, 2020
First decision: July 29, 2020
Revised: August 12, 2020
Accepted: September 12, 2020
Article in press: September 12, 2020
Published online: October 14, 2020
Processing time: 139 Days and 15.1 Hours
Core Tip
Core Tip: Computer aided diagnosis of oesophageal pathology may potentially be an adjunct for the endoscopist which will improve the detection of early neoplasia in Barrett’s oesophagus and early squamous neoplasia such that curative endoscopic therapy can be offered. There are significant miss rates of oesophageal cancers despite advances in endoscopic imaging modalities and an artificial intelligence (AI) tool will off-set human factors associated with some miss rates. To fulfil the potential of this exciting area of AI certain criteria need to be met which we will expand upon. Once implemented this will have a significant impact on this field of endoscopy.