Publication Name	Artificial Intelligence in Gastrointestinal Endoscopy
Manuscript ID	66020
Country	Singapore

Received	2021-03-19 09:18
Peer-Review Started	2021-03-19 09:22
To Make the First Decision
Return for Revision	2021-03-26 03:46
Revised	2021-03-27 13:59
Second Decision	2021-04-19 08:09
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2021-04-20 05:01
Articles in Press	2021-04-20 05:01
Publication Fee Transferred
Edit the Manuscript by Language Editor	2021-04-28 01:25
Typeset the Manuscript	2021-04-28 09:01
Publish the Manuscript Online	2021-04-28 12:41

ISSN	2689-7164 (online)
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/
Copyright	© The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
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Website	http://www.wjgnet.com

Category	Gastroenterology & Hepatology
Manuscript Type	Minireviews
Article Title	Colonoscopy and artificial intelligence: Bridging the gap or a gap needing to be bridged?
Manuscript Source	Invited Manuscript
All Author List	James Weiquan Li and Tiing Leong Ang
ORCID	Author(s) ORCID Number James Weiquan Li http://orcid.org/0000-0002-5241-4278 Tiing Leong Ang http://orcid.org/0000-0001-9993-8549
Funding Agency and Grant Number
Corresponding Author	Tiing Leong Ang, FASGE, FRCP, MBBS, Chief Physician, Professor, Department of Gastroenterology and Hepatology, Changi General Hospital, 2 Simei Street 3, Singapore 529889, Singapore. ang.tiing.leong@singhealth.com.sg
Key Words	Artificial intelligence; Endoscopy; Colonoscopy; Detection; Diagnosis
Core Tip	The use of artificial intelligence (AI) for colonoscopy has been studied most extensively for polyp detection and characterization. Despite advances made in this field, AI systems studied for these purposes represent only the machine learning domain of AI, and individual machine learning algorithms used in these studies are each focused on performing a very narrow task. While they may bridge existing gaps in polyp detection and real-time optical diagnosis of colorectal polyps, the introduction of AI into colonoscopy will also mean that there are new gaps which must be bridged for AI systems to be routinely used in clinical practice.
Publish Date	2021-04-28 12:41
Citation	Ang TL, Li JW. Colonoscopy and artificial intelligence: Bridging the gap or a gap needing to be bridged? Artif Intell Gastrointest Endosc 2021; 2(2): 36-49
URL	https://www.wjgnet.com/2689-7164/full/v2/i2/36.htm
DOI	https://dx.doi.org/10.37126/aige.v2.i2.36

Full Article (PDF)	AIGE-2-36.pdf
Full Article (Word)	AIGE-2-36.docx
Manuscript File	66020-Review-FilipodiaCL.docx
Answering Reviewers	66020-Answering reviewers.pdf
Audio Core Tip	66020-Audio core tip.m4a
Conflict-of-Interest Disclosure Form	66020-Conflict-of-interest statement.pdf
Copyright License Agreement	66020-Copyright license agreement.pdf
Non-Native Speakers of English Editing Certificate	66020-Language certificate.pdf
Peer-review Report	66020-Peer-review(s).pdf
Scientific Misconduct Check	66020-Scientific misconduct check.pdf
Scientific Editor Work List	66020-Scientific editor work list.pdf
CrossCheck Report	66020-CrossCheck report.pdf