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Artificial intelligence for the early detection of colorectal cancer: A comprehensive review of its advantages and misconceptions
Colorectal cancer (CRC) was the second-ranked worldwide type of cancer during 2020 due to the crude mortality rate of 12.0 per 100000 inhabitants. It can be prevented if glandular tissue (adenomatous polyps) is detected early. Colonoscopy has been strongly recommended as a screening test for both ea...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8517786/ https://www.ncbi.nlm.nih.gov/pubmed/34720530 http://dx.doi.org/10.3748/wjg.v27.i38.6399 |
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author | Viscaino, Michelle Torres Bustos, Javier Muñoz, Pablo Auat Cheein, Cecilia Cheein, Fernando Auat |
author_facet | Viscaino, Michelle Torres Bustos, Javier Muñoz, Pablo Auat Cheein, Cecilia Cheein, Fernando Auat |
author_sort | Viscaino, Michelle |
collection | PubMed |
description | Colorectal cancer (CRC) was the second-ranked worldwide type of cancer during 2020 due to the crude mortality rate of 12.0 per 100000 inhabitants. It can be prevented if glandular tissue (adenomatous polyps) is detected early. Colonoscopy has been strongly recommended as a screening test for both early cancer and adenomatous polyps. However, it has some limitations that include the high polyp miss rate for smaller (< 10 mm) or flat polyps, which are easily missed during visual inspection. Due to the rapid advancement of technology, artificial intelligence (AI) has been a thriving area in different fields, including medicine. Particularly, in gastroenterology AI software has been included in computer-aided systems for diagnosis and to improve the assertiveness of automatic polyp detection and its classification as a preventive method for CRC. This article provides an overview of recent research focusing on AI tools and their applications in the early detection of CRC and adenomatous polyps, as well as an insightful analysis of the main advantages and misconceptions in the field. |
format | Online Article Text |
id | pubmed-8517786 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-85177862021-10-28 Artificial intelligence for the early detection of colorectal cancer: A comprehensive review of its advantages and misconceptions Viscaino, Michelle Torres Bustos, Javier Muñoz, Pablo Auat Cheein, Cecilia Cheein, Fernando Auat World J Gastroenterol Minireviews Colorectal cancer (CRC) was the second-ranked worldwide type of cancer during 2020 due to the crude mortality rate of 12.0 per 100000 inhabitants. It can be prevented if glandular tissue (adenomatous polyps) is detected early. Colonoscopy has been strongly recommended as a screening test for both early cancer and adenomatous polyps. However, it has some limitations that include the high polyp miss rate for smaller (< 10 mm) or flat polyps, which are easily missed during visual inspection. Due to the rapid advancement of technology, artificial intelligence (AI) has been a thriving area in different fields, including medicine. Particularly, in gastroenterology AI software has been included in computer-aided systems for diagnosis and to improve the assertiveness of automatic polyp detection and its classification as a preventive method for CRC. This article provides an overview of recent research focusing on AI tools and their applications in the early detection of CRC and adenomatous polyps, as well as an insightful analysis of the main advantages and misconceptions in the field. Baishideng Publishing Group Inc 2021-10-14 2021-10-14 /pmc/articles/PMC8517786/ /pubmed/34720530 http://dx.doi.org/10.3748/wjg.v27.i38.6399 Text en ©The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved. https://creativecommons.org/licenses/by-nc/4.0/This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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. |
spellingShingle | Minireviews Viscaino, Michelle Torres Bustos, Javier Muñoz, Pablo Auat Cheein, Cecilia Cheein, Fernando Auat Artificial intelligence for the early detection of colorectal cancer: A comprehensive review of its advantages and misconceptions |
title | Artificial intelligence for the early detection of colorectal cancer: A comprehensive review of its advantages and misconceptions |
title_full | Artificial intelligence for the early detection of colorectal cancer: A comprehensive review of its advantages and misconceptions |
title_fullStr | Artificial intelligence for the early detection of colorectal cancer: A comprehensive review of its advantages and misconceptions |
title_full_unstemmed | Artificial intelligence for the early detection of colorectal cancer: A comprehensive review of its advantages and misconceptions |
title_short | Artificial intelligence for the early detection of colorectal cancer: A comprehensive review of its advantages and misconceptions |
title_sort | artificial intelligence for the early detection of colorectal cancer: a comprehensive review of its advantages and misconceptions |
topic | Minireviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8517786/ https://www.ncbi.nlm.nih.gov/pubmed/34720530 http://dx.doi.org/10.3748/wjg.v27.i38.6399 |
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