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9/28/2020 7:42:41 AM | Browse: 734 | Download: 961
Publication Name World Journal of Gastroenterology
Manuscript ID 57242
Country/Territory Italy
Received
2020-06-02 22:44
Peer-Review Started
2020-06-02 22:45
To Make the First Decision
Return for Revision
2020-06-12 17:21
Revised
2020-06-30 00:28
Second Decision
2020-09-15 11:57
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2020-09-15 23:40
Articles in Press
2020-09-15 23:40
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript
2020-09-24 03:26
Publish the Manuscript Online
2020-09-28 07:42
ISSN 1007-9327 (print) and 2219-2840 (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) 2020. Published by Baishideng Publishing Group Inc. All rights reserved.
Article Reprints For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
Permissions For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website http://www.wjgnet.com
Category Gastroenterology & Hepatology
Manuscript Type Minireviews
Article Title Artificial intelligence technologies for the detection of colorectal lesions: The future is now
Manuscript Source Invited Manuscript
All Author List Simona Attardo, Viveksandeep Thoguluva Chandrasekar, Marco Spadaccini, Roberta Maselli, Harsh K Patel, Madhav Desai, Antonio Capogreco, Matteo Badalamenti, Piera Alessia Galtieri, Gaia Pellegatta, Alessandro Fugazza, Silvia Carrara, Andrea Anderloni, Pietro Occhipinti, Cesare Hassan, Prateek Sharma and Alessandro Repici
ORCID
Author(s) ORCID Number
Simona Attardo http://orcid.org/0000-0003-0232-3682
Viveksandeep Thoguluva Chandrasekar http://orcid.org/0000-0001-5256-4113
Marco Spadaccini http://orcid.org/0000-0003-3909-9012
Roberta Maselli http://orcid.org/0000-0001-7291-9110
Harsh K Patel http://orcid.org/0000-0002-9180-2150
Madhav Desai http://orcid.org/0000-0001-8871-3627
Antonio Capogreco http://orcid.org/0000-0002-2212-2266
Matteo Badalamenti http://orcid.org/0000-0002-95439862
Piera Alessia Galtieri http://orcid.org/0000-0002-3253-6972
Gaia Pellegatta http://orcid.org/0000-0003-0235-4905
Alessandro Fugazza http://orcid.org/0000-0003-0485-4903
Silvia Carrara http://orcid.org/0000-0003-4206-9463
Andrea Anderloni http://orcid.org/0000-0002-1021-0031
Pietro Occhipinti http://orcid.org/0000-0001-7048-4600
Cesare Hassan http://orcid.org/0000-0001-7167-1459
Prateek Sharma http://orcid.org/0000-0003-4003-7548
Alessandro Repici http://orcid.org/0000-0002-1621-6450
Funding Agency and Grant Number
Corresponding Author Marco Spadaccini, MD, Doctor, Department of Endoscopy, Humanitas Research Hospital, via Manzoni 56, Rozzano 20089, Italy. marco.spadaccini@humanitas.it
Key Words Endoscopy; Colonoscopy; Screening; Surveillance; Technology; Artificial intelligence
Core Tip The use of artificial intelligence (AI) in colonoscopy has been gaining popularity in current times. At first, the efficacy of deep convolutional neural network (DCNN)-based AI system for polyp detection has been tested in ex vivo settings such as still images or videos from colonoscopies. Recent trials have evaluated the real-time efficacy of DCNN-based systems in improving adenoma detection rate and polyp detection rate. In this review we reported all the preliminary ex vivo experiences and summarized the promising results of the initial randomized controlled trials.
Publish Date 2020-09-28 07:42
Citation Attardo S, Chandrasekar VT, Spadaccini M, Maselli R, Patel HK, Desai M, Capogreco A, Badalamenti M, Galtieri PA, Pellegatta G, Fugazza A, Carrara S, Anderloni A, Occhipinti P, Hassan C, Sharma P, Repici A. Artificial intelligence technologies for the detection of colorectal lesions: The future is now. World J Gastroenterol 2020; 26(37): 5606-5616
URL https://www.wjgnet.com/1007-9327/full/v26/i37/5606.htm
DOI https://dx.doi.org/10.3748/wjg.v26.i37.5606
Full Article (PDF) WJG-26-5606.pdf
Full Article (Word) WJG-26-5606.docx
Manuscript File 57242-Review.docx
Answering Reviewers 57242-Answering reviewers.pdf
Audio Core Tip 57242-Audio core tip.m4a
Conflict-of-Interest Disclosure Form 57242-Conflict-of-interest statement.pdf
Copyright License Agreement 57242-Copyright license agreement.pdf
Non-Native Speakers of English Editing Certificate 57242-Language certificate.pdf
Peer-review Report 57242-Peer-review(s).pdf
Scientific Misconduct Check 57242-Scientific misconduct check.pdf
Scientific Editor Work List 57242-Scientific editor work list.pdf