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9/15/2020 11:40:28 PM | Browse: 154 | Download: 230
Publication Name World Journal of Gastroenterology
Manuscript ID 57242
Country/Territory Italy
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
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.
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
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
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.
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