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Artificial intelligence in gastrointestinal endoscopy: The future is almost here
Artificial intelligence (AI) enables machines to provide unparalleled value in a myriad of industries and applications. In recent years, researchers have harnessed artificial intelligence to analyze large-volume, unstructured medical data and perform clinical tasks, such as the identification of dia...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6198310/ https://www.ncbi.nlm.nih.gov/pubmed/30364792 http://dx.doi.org/10.4253/wjge.v10.i10.239 |
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author | Alagappan, Muthuraman Brown, Jeremy R Glissen Mori, Yuichi Berzin, Tyler M |
author_facet | Alagappan, Muthuraman Brown, Jeremy R Glissen Mori, Yuichi Berzin, Tyler M |
author_sort | Alagappan, Muthuraman |
collection | PubMed |
description | Artificial intelligence (AI) enables machines to provide unparalleled value in a myriad of industries and applications. In recent years, researchers have harnessed artificial intelligence to analyze large-volume, unstructured medical data and perform clinical tasks, such as the identification of diabetic retinopathy or the diagnosis of cutaneous malignancies. Applications of artificial intelligence techniques, specifically machine learning and more recently deep learning, are beginning to emerge in gastrointestinal endoscopy. The most promising of these efforts have been in computer-aided detection and computer-aided diagnosis of colorectal polyps, with recent systems demonstrating high sensitivity and accuracy even when compared to expert human endoscopists. AI has also been utilized to identify gastrointestinal bleeding, to detect areas of inflammation, and even to diagnose certain gastrointestinal infections. Future work in the field should concentrate on creating seamless integration of AI systems with current endoscopy platforms and electronic medical records, developing training modules to teach clinicians how to use AI tools, and determining the best means for regulation and approval of new AI technology. |
format | Online Article Text |
id | pubmed-6198310 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-61983102018-10-24 Artificial intelligence in gastrointestinal endoscopy: The future is almost here Alagappan, Muthuraman Brown, Jeremy R Glissen Mori, Yuichi Berzin, Tyler M World J Gastrointest Endosc Review Artificial intelligence (AI) enables machines to provide unparalleled value in a myriad of industries and applications. In recent years, researchers have harnessed artificial intelligence to analyze large-volume, unstructured medical data and perform clinical tasks, such as the identification of diabetic retinopathy or the diagnosis of cutaneous malignancies. Applications of artificial intelligence techniques, specifically machine learning and more recently deep learning, are beginning to emerge in gastrointestinal endoscopy. The most promising of these efforts have been in computer-aided detection and computer-aided diagnosis of colorectal polyps, with recent systems demonstrating high sensitivity and accuracy even when compared to expert human endoscopists. AI has also been utilized to identify gastrointestinal bleeding, to detect areas of inflammation, and even to diagnose certain gastrointestinal infections. Future work in the field should concentrate on creating seamless integration of AI systems with current endoscopy platforms and electronic medical records, developing training modules to teach clinicians how to use AI tools, and determining the best means for regulation and approval of new AI technology. Baishideng Publishing Group Inc 2018-10-16 2018-10-16 /pmc/articles/PMC6198310/ /pubmed/30364792 http://dx.doi.org/10.4253/wjge.v10.i10.239 Text en ©The Author(s) 2018. Published by Baishideng Publishing Group Inc. All rights reserved. http://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 | Review Alagappan, Muthuraman Brown, Jeremy R Glissen Mori, Yuichi Berzin, Tyler M Artificial intelligence in gastrointestinal endoscopy: The future is almost here |
title | Artificial intelligence in gastrointestinal endoscopy: The future is almost here |
title_full | Artificial intelligence in gastrointestinal endoscopy: The future is almost here |
title_fullStr | Artificial intelligence in gastrointestinal endoscopy: The future is almost here |
title_full_unstemmed | Artificial intelligence in gastrointestinal endoscopy: The future is almost here |
title_short | Artificial intelligence in gastrointestinal endoscopy: The future is almost here |
title_sort | artificial intelligence in gastrointestinal endoscopy: the future is almost here |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6198310/ https://www.ncbi.nlm.nih.gov/pubmed/30364792 http://dx.doi.org/10.4253/wjge.v10.i10.239 |
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