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Artificial Intelligence in Digestive Endoscopy—Where Are We and Where Are We Going?
Artificial intelligence, a computer-based concept that tries to mimic human thinking, is slowly becoming part of the endoscopy lab. It has developed considerably since the first attempt at developing an automated medical diagnostic tool, today being adopted in almost all medical fields, digestive en...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9029251/ https://www.ncbi.nlm.nih.gov/pubmed/35453975 http://dx.doi.org/10.3390/diagnostics12040927 |
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author | Vulpoi, Radu-Alexandru Luca, Mihaela Ciobanu, Adrian Olteanu, Andrei Barboi, Oana-Bogdana Drug, Vasile Liviu |
author_facet | Vulpoi, Radu-Alexandru Luca, Mihaela Ciobanu, Adrian Olteanu, Andrei Barboi, Oana-Bogdana Drug, Vasile Liviu |
author_sort | Vulpoi, Radu-Alexandru |
collection | PubMed |
description | Artificial intelligence, a computer-based concept that tries to mimic human thinking, is slowly becoming part of the endoscopy lab. It has developed considerably since the first attempt at developing an automated medical diagnostic tool, today being adopted in almost all medical fields, digestive endoscopy included. The detection rate of preneoplastic lesions (i.e., polyps) during colonoscopy may be increased with artificial intelligence assistance. It has also proven useful in detecting signs of ulcerative colitis activity. In upper digestive endoscopy, deep learning models may prove to be useful in the diagnosis and management of upper digestive tract diseases, such as gastroesophageal reflux disease, Barrett’s esophagus, and gastric cancer. As is the case with all new medical devices, there are challenges in the implementation in daily medical practice. The regulatory, economic, organizational culture, and language barriers between humans and machines are a few of them. Even so, many devices have been approved for use by their respective regulators. Future studies are currently striving to develop deep learning models that can replicate a growing amount of human brain activity. In conclusion, artificial intelligence may become an indispensable tool in digestive endoscopy. |
format | Online Article Text |
id | pubmed-9029251 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-90292512022-04-23 Artificial Intelligence in Digestive Endoscopy—Where Are We and Where Are We Going? Vulpoi, Radu-Alexandru Luca, Mihaela Ciobanu, Adrian Olteanu, Andrei Barboi, Oana-Bogdana Drug, Vasile Liviu Diagnostics (Basel) Review Artificial intelligence, a computer-based concept that tries to mimic human thinking, is slowly becoming part of the endoscopy lab. It has developed considerably since the first attempt at developing an automated medical diagnostic tool, today being adopted in almost all medical fields, digestive endoscopy included. The detection rate of preneoplastic lesions (i.e., polyps) during colonoscopy may be increased with artificial intelligence assistance. It has also proven useful in detecting signs of ulcerative colitis activity. In upper digestive endoscopy, deep learning models may prove to be useful in the diagnosis and management of upper digestive tract diseases, such as gastroesophageal reflux disease, Barrett’s esophagus, and gastric cancer. As is the case with all new medical devices, there are challenges in the implementation in daily medical practice. The regulatory, economic, organizational culture, and language barriers between humans and machines are a few of them. Even so, many devices have been approved for use by their respective regulators. Future studies are currently striving to develop deep learning models that can replicate a growing amount of human brain activity. In conclusion, artificial intelligence may become an indispensable tool in digestive endoscopy. MDPI 2022-04-08 /pmc/articles/PMC9029251/ /pubmed/35453975 http://dx.doi.org/10.3390/diagnostics12040927 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Vulpoi, Radu-Alexandru Luca, Mihaela Ciobanu, Adrian Olteanu, Andrei Barboi, Oana-Bogdana Drug, Vasile Liviu Artificial Intelligence in Digestive Endoscopy—Where Are We and Where Are We Going? |
title | Artificial Intelligence in Digestive Endoscopy—Where Are We and Where Are We Going? |
title_full | Artificial Intelligence in Digestive Endoscopy—Where Are We and Where Are We Going? |
title_fullStr | Artificial Intelligence in Digestive Endoscopy—Where Are We and Where Are We Going? |
title_full_unstemmed | Artificial Intelligence in Digestive Endoscopy—Where Are We and Where Are We Going? |
title_short | Artificial Intelligence in Digestive Endoscopy—Where Are We and Where Are We Going? |
title_sort | artificial intelligence in digestive endoscopy—where are we and where are we going? |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9029251/ https://www.ncbi.nlm.nih.gov/pubmed/35453975 http://dx.doi.org/10.3390/diagnostics12040927 |
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