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Implementation of artificial intelligence in upper gastrointestinal endoscopy

The application of artificial intelligence (AI) using deep learning has significantly expanded in the field of esophagogastric endoscopy. Recent studies have shown promising results in detecting and differentiating early gastric cancer using AI tools built using white light, magnified, or image‐enha...

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Detalles Bibliográficos
Autores principales: Nagao, Sayaka, Tani, Yasuhiro, Shibata, Junichi, Tsuji, Yosuke, Tada, Tomohiro, Ishihara, Ryu, Fujishiro, Mitsuhiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9302271/
https://www.ncbi.nlm.nih.gov/pubmed/35873509
http://dx.doi.org/10.1002/deo2.72
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author Nagao, Sayaka
Tani, Yasuhiro
Shibata, Junichi
Tsuji, Yosuke
Tada, Tomohiro
Ishihara, Ryu
Fujishiro, Mitsuhiro
author_facet Nagao, Sayaka
Tani, Yasuhiro
Shibata, Junichi
Tsuji, Yosuke
Tada, Tomohiro
Ishihara, Ryu
Fujishiro, Mitsuhiro
author_sort Nagao, Sayaka
collection PubMed
description The application of artificial intelligence (AI) using deep learning has significantly expanded in the field of esophagogastric endoscopy. Recent studies have shown promising results in detecting and differentiating early gastric cancer using AI tools built using white light, magnified, or image‐enhanced endoscopic images. Some studies have reported the use of AI tools to predict the depth of early gastric cancer based on endoscopic images. Similarly, studies based on using AI for detecting early esophageal cancer have also been reported, with an accuracy comparable to that of endoscopy specialists. Moreover, an AI system, developed to diagnose pharyngeal cancer, has shown promising performance with high sensitivity. These reports suggest that, if introduced for regular use in clinical settings, AI systems can significantly reduce the burden on physicians. This review summarizes the current status of AI applications in the upper gastrointestinal tract and presents directions for clinical practice implementation and future research.
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spelling pubmed-93022712022-07-22 Implementation of artificial intelligence in upper gastrointestinal endoscopy Nagao, Sayaka Tani, Yasuhiro Shibata, Junichi Tsuji, Yosuke Tada, Tomohiro Ishihara, Ryu Fujishiro, Mitsuhiro DEN Open Reviews The application of artificial intelligence (AI) using deep learning has significantly expanded in the field of esophagogastric endoscopy. Recent studies have shown promising results in detecting and differentiating early gastric cancer using AI tools built using white light, magnified, or image‐enhanced endoscopic images. Some studies have reported the use of AI tools to predict the depth of early gastric cancer based on endoscopic images. Similarly, studies based on using AI for detecting early esophageal cancer have also been reported, with an accuracy comparable to that of endoscopy specialists. Moreover, an AI system, developed to diagnose pharyngeal cancer, has shown promising performance with high sensitivity. These reports suggest that, if introduced for regular use in clinical settings, AI systems can significantly reduce the burden on physicians. This review summarizes the current status of AI applications in the upper gastrointestinal tract and presents directions for clinical practice implementation and future research. John Wiley and Sons Inc. 2022-03-15 /pmc/articles/PMC9302271/ /pubmed/35873509 http://dx.doi.org/10.1002/deo2.72 Text en © 2022 The Authors. DEN Open published by John Wiley & Sons Australia, Ltd on behalf of Japan Gastroenterological Endoscopy Society https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Reviews
Nagao, Sayaka
Tani, Yasuhiro
Shibata, Junichi
Tsuji, Yosuke
Tada, Tomohiro
Ishihara, Ryu
Fujishiro, Mitsuhiro
Implementation of artificial intelligence in upper gastrointestinal endoscopy
title Implementation of artificial intelligence in upper gastrointestinal endoscopy
title_full Implementation of artificial intelligence in upper gastrointestinal endoscopy
title_fullStr Implementation of artificial intelligence in upper gastrointestinal endoscopy
title_full_unstemmed Implementation of artificial intelligence in upper gastrointestinal endoscopy
title_short Implementation of artificial intelligence in upper gastrointestinal endoscopy
title_sort implementation of artificial intelligence in upper gastrointestinal endoscopy
topic Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9302271/
https://www.ncbi.nlm.nih.gov/pubmed/35873509
http://dx.doi.org/10.1002/deo2.72
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