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10/12/2021 7:00:09 AM | Browse: 486 | Download: 732
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Received |
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2021-02-28 21:29 |
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Peer-Review Started |
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2021-02-28 21:33 |
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To Make the First Decision |
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Return for Revision |
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2021-03-27 21:39 |
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Revised |
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2021-04-26 21:39 |
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Second Decision |
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2021-09-13 02:28 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2021-09-16 23:53 |
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Articles in Press |
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2021-09-16 23:53 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2021-10-11 00:10 |
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Publish the Manuscript Online |
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2021-10-12 06:53 |
| 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) 2021. Published by Baishideng Publishing Group Inc. All rights reserved. |
| Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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| Permissions |
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 |
Engineering, Biomedical |
| Manuscript Type |
Minireviews |
| Article Title |
Artificial intelligence for the early detection of colorectal cancer: A comprehensive review of its advantages and misconceptions
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Michelle Viscaino, Javier Torres Bustos, Pablo Muñoz, Cecilia Auat Cheein and Fernando Auat Cheein |
| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| Chilean National Agency for Research and Development (ANID) |
FB0008 |
| CONICYT-PCHA/Doctorado Nacional |
2018-21181420 |
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| Corresponding Author |
Fernando Auat Cheein, PhD, Associate Professor, Department of Electronic Engineering, Universidad Técnica Federico Santa María, Av. España 1680, Valparaiso 2340000, Chile. fernando.auat@usm.cl |
| Key Words |
Artificial intelligence; Machine learning; Deep learning; Medical images; Colorectal cancer; Colorectal polyps |
| Core Tip |
Artificial intelligence-based (AI) methods have demonstrated high performance in classification, object detection, and segmentation tasks. Through multidisciplinary and collaborative work between clinicians and technicians, the advantages of AI have been successfully applied in automatic polyp detection and classification. The new AI-based systems present a better polyp detection rate and contribute to better clinical decision-making for preventing colorectal cancer (CRC). This article provides an overview of recent research focusing on AI and its applications in the early detection of CRC and adenomatous polyps. |
| Publish Date |
2021-10-12 06:53 |
| Citation |
Viscaino M, Torres Bustos J, Muñoz P, Auat Cheein C, Cheein FA. Artificial intelligence for the early detection of colorectal cancer: A comprehensive review of its advantages and misconceptions. World J Gastroenterol 2021; 27(38): 6399-6414 |
| URL |
https://www.wjgnet.com/1007-9327/full/v27/i38/6399.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v27.i38.6399 |
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