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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For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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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
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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 |
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Funding Agency and Grant Number |
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Corresponding Author |
Marco Spadaccini, MD, Doctor, 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 |