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Artificial intelligence in colonoscopy

Colorectal cancer remains a leading cause of morbidity and mortality in the United States. Advances in artificial intelligence (AI), specifically computer aided detection and computer-aided diagnosis offer promising methods of increasing adenoma detection rates with the goal of removing more pre-can...

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Detalles Bibliográficos
Autores principales: Joseph, Joel, LePage, Ella Marie, Cheney, Catherine Phillips, Pawa, Rishi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Baishideng Publishing Group Inc 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371500/
https://www.ncbi.nlm.nih.gov/pubmed/34447227
http://dx.doi.org/10.3748/wjg.v27.i29.4802
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author Joseph, Joel
LePage, Ella Marie
Cheney, Catherine Phillips
Pawa, Rishi
author_facet Joseph, Joel
LePage, Ella Marie
Cheney, Catherine Phillips
Pawa, Rishi
author_sort Joseph, Joel
collection PubMed
description Colorectal cancer remains a leading cause of morbidity and mortality in the United States. Advances in artificial intelligence (AI), specifically computer aided detection and computer-aided diagnosis offer promising methods of increasing adenoma detection rates with the goal of removing more pre-cancerous polyps. Conversely, these methods also may allow for smaller non-cancerous lesions to be diagnosed in vivo and left in place, decreasing the risks that come with unnecessary polypectomies. This review will provide an overview of current advances in the use of AI in colonoscopy to aid in polyp detection and characterization as well as areas of developing research.
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spelling pubmed-83715002021-08-25 Artificial intelligence in colonoscopy Joseph, Joel LePage, Ella Marie Cheney, Catherine Phillips Pawa, Rishi World J Gastroenterol Minireviews Colorectal cancer remains a leading cause of morbidity and mortality in the United States. Advances in artificial intelligence (AI), specifically computer aided detection and computer-aided diagnosis offer promising methods of increasing adenoma detection rates with the goal of removing more pre-cancerous polyps. Conversely, these methods also may allow for smaller non-cancerous lesions to be diagnosed in vivo and left in place, decreasing the risks that come with unnecessary polypectomies. This review will provide an overview of current advances in the use of AI in colonoscopy to aid in polyp detection and characterization as well as areas of developing research. Baishideng Publishing Group Inc 2021-08-07 2021-08-07 /pmc/articles/PMC8371500/ /pubmed/34447227 http://dx.doi.org/10.3748/wjg.v27.i29.4802 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 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/
spellingShingle Minireviews
Joseph, Joel
LePage, Ella Marie
Cheney, Catherine Phillips
Pawa, Rishi
Artificial intelligence in colonoscopy
title Artificial intelligence in colonoscopy
title_full Artificial intelligence in colonoscopy
title_fullStr Artificial intelligence in colonoscopy
title_full_unstemmed Artificial intelligence in colonoscopy
title_short Artificial intelligence in colonoscopy
title_sort artificial intelligence in colonoscopy
topic Minireviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371500/
https://www.ncbi.nlm.nih.gov/pubmed/34447227
http://dx.doi.org/10.3748/wjg.v27.i29.4802
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