Cargando…
Use of Artificial Intelligence to Improve the Quality Control of Gastrointestinal Endoscopy
With the rapid development of science and technology, artificial intelligence (AI) systems are becoming ubiquitous, and their utility in gastroenteroscopy is beginning to be recognized. Digestive endoscopy is a conventional and reliable method of examining and diagnosing digestive tract diseases. Ho...
Autores principales: | , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8339701/ https://www.ncbi.nlm.nih.gov/pubmed/34368199 http://dx.doi.org/10.3389/fmed.2021.709347 |
_version_ | 1783733645835501568 |
---|---|
author | Song, Ya-qi Mao, Xin-li Zhou, Xian-bin He, Sai-qin Chen, Ya-hong Zhang, Li-hui Xu, Shi-wen Yan, Ling-ling Tang, Shen-ping Ye, Li-ping Li, Shao-wei |
author_facet | Song, Ya-qi Mao, Xin-li Zhou, Xian-bin He, Sai-qin Chen, Ya-hong Zhang, Li-hui Xu, Shi-wen Yan, Ling-ling Tang, Shen-ping Ye, Li-ping Li, Shao-wei |
author_sort | Song, Ya-qi |
collection | PubMed |
description | With the rapid development of science and technology, artificial intelligence (AI) systems are becoming ubiquitous, and their utility in gastroenteroscopy is beginning to be recognized. Digestive endoscopy is a conventional and reliable method of examining and diagnosing digestive tract diseases. However, with the increase in the number and types of endoscopy, problems such as a lack of skilled endoscopists and difference in the professional skill of doctors with different degrees of experience have become increasingly apparent. Most studies thus far have focused on using computers to detect and diagnose lesions, but improving the quality of endoscopic examination process itself is the basis for improving the detection rate and correctly diagnosing diseases. In the present study, we mainly reviewed the role of AI in monitoring systems, mainly through the endoscopic examination time, reducing the blind spot rate, improving the success rate for detecting high-risk lesions, evaluating intestinal preparation, increasing the detection rate of polyps, automatically collecting maps and writing reports. AI can even perform quality control evaluations for endoscopists, improve the detection rate of endoscopic lesions and reduce the burden on endoscopists. |
format | Online Article Text |
id | pubmed-8339701 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-83397012021-08-06 Use of Artificial Intelligence to Improve the Quality Control of Gastrointestinal Endoscopy Song, Ya-qi Mao, Xin-li Zhou, Xian-bin He, Sai-qin Chen, Ya-hong Zhang, Li-hui Xu, Shi-wen Yan, Ling-ling Tang, Shen-ping Ye, Li-ping Li, Shao-wei Front Med (Lausanne) Medicine With the rapid development of science and technology, artificial intelligence (AI) systems are becoming ubiquitous, and their utility in gastroenteroscopy is beginning to be recognized. Digestive endoscopy is a conventional and reliable method of examining and diagnosing digestive tract diseases. However, with the increase in the number and types of endoscopy, problems such as a lack of skilled endoscopists and difference in the professional skill of doctors with different degrees of experience have become increasingly apparent. Most studies thus far have focused on using computers to detect and diagnose lesions, but improving the quality of endoscopic examination process itself is the basis for improving the detection rate and correctly diagnosing diseases. In the present study, we mainly reviewed the role of AI in monitoring systems, mainly through the endoscopic examination time, reducing the blind spot rate, improving the success rate for detecting high-risk lesions, evaluating intestinal preparation, increasing the detection rate of polyps, automatically collecting maps and writing reports. AI can even perform quality control evaluations for endoscopists, improve the detection rate of endoscopic lesions and reduce the burden on endoscopists. Frontiers Media S.A. 2021-07-22 /pmc/articles/PMC8339701/ /pubmed/34368199 http://dx.doi.org/10.3389/fmed.2021.709347 Text en Copyright © 2021 Song, Mao, Zhou, He, Chen, Zhang, Xu, Yan, Tang, Ye and Li. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Medicine Song, Ya-qi Mao, Xin-li Zhou, Xian-bin He, Sai-qin Chen, Ya-hong Zhang, Li-hui Xu, Shi-wen Yan, Ling-ling Tang, Shen-ping Ye, Li-ping Li, Shao-wei Use of Artificial Intelligence to Improve the Quality Control of Gastrointestinal Endoscopy |
title | Use of Artificial Intelligence to Improve the Quality Control of Gastrointestinal Endoscopy |
title_full | Use of Artificial Intelligence to Improve the Quality Control of Gastrointestinal Endoscopy |
title_fullStr | Use of Artificial Intelligence to Improve the Quality Control of Gastrointestinal Endoscopy |
title_full_unstemmed | Use of Artificial Intelligence to Improve the Quality Control of Gastrointestinal Endoscopy |
title_short | Use of Artificial Intelligence to Improve the Quality Control of Gastrointestinal Endoscopy |
title_sort | use of artificial intelligence to improve the quality control of gastrointestinal endoscopy |
topic | Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8339701/ https://www.ncbi.nlm.nih.gov/pubmed/34368199 http://dx.doi.org/10.3389/fmed.2021.709347 |
work_keys_str_mv | AT songyaqi useofartificialintelligencetoimprovethequalitycontrolofgastrointestinalendoscopy AT maoxinli useofartificialintelligencetoimprovethequalitycontrolofgastrointestinalendoscopy AT zhouxianbin useofartificialintelligencetoimprovethequalitycontrolofgastrointestinalendoscopy AT hesaiqin useofartificialintelligencetoimprovethequalitycontrolofgastrointestinalendoscopy AT chenyahong useofartificialintelligencetoimprovethequalitycontrolofgastrointestinalendoscopy AT zhanglihui useofartificialintelligencetoimprovethequalitycontrolofgastrointestinalendoscopy AT xushiwen useofartificialintelligencetoimprovethequalitycontrolofgastrointestinalendoscopy AT yanlingling useofartificialintelligencetoimprovethequalitycontrolofgastrointestinalendoscopy AT tangshenping useofartificialintelligencetoimprovethequalitycontrolofgastrointestinalendoscopy AT yeliping useofartificialintelligencetoimprovethequalitycontrolofgastrointestinalendoscopy AT lishaowei useofartificialintelligencetoimprovethequalitycontrolofgastrointestinalendoscopy |