Cargando…
Artificial intelligence-assisted endoscopic detection of esophageal neoplasia in early stage: The next step?
Esophageal cancer (EC) is a common malignant tumor of the digestive tract and originates from the epithelium of the esophageal mucosa. It has been confirmed that early EC lesions can be cured by endoscopic therapy, and the curative effect is equivalent to that of surgical operation. Upper gastrointe...
Autor principal: | |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8047537/ https://www.ncbi.nlm.nih.gov/pubmed/33911463 http://dx.doi.org/10.3748/wjg.v27.i14.1392 |
_version_ | 1783679060723892224 |
---|---|
author | Liu, Yong |
author_facet | Liu, Yong |
author_sort | Liu, Yong |
collection | PubMed |
description | Esophageal cancer (EC) is a common malignant tumor of the digestive tract and originates from the epithelium of the esophageal mucosa. It has been confirmed that early EC lesions can be cured by endoscopic therapy, and the curative effect is equivalent to that of surgical operation. Upper gastrointestinal endoscopy is still the gold standard for EC diagnosis. The accuracy of endoscopic examination results largely depends on the professional level of the examiner. Artificial intelligence (AI) has been applied in the screening of early EC and has shown advantages; notably, it is more accurate than less-experienced endoscopists. This paper reviews the application of AI in the field of endoscopic detection of early EC, including squamous cell carcinoma and adenocarcinoma, and describes the relevant progress. Although up to now most of the studies evaluating the clinical application of AI in early EC endoscopic detection are focused on still images, AI-assisted real-time detection based on live-stream video may be the next step. |
format | Online Article Text |
id | pubmed-8047537 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-80475372021-04-27 Artificial intelligence-assisted endoscopic detection of esophageal neoplasia in early stage: The next step? Liu, Yong World J Gastroenterol Minireviews Esophageal cancer (EC) is a common malignant tumor of the digestive tract and originates from the epithelium of the esophageal mucosa. It has been confirmed that early EC lesions can be cured by endoscopic therapy, and the curative effect is equivalent to that of surgical operation. Upper gastrointestinal endoscopy is still the gold standard for EC diagnosis. The accuracy of endoscopic examination results largely depends on the professional level of the examiner. Artificial intelligence (AI) has been applied in the screening of early EC and has shown advantages; notably, it is more accurate than less-experienced endoscopists. This paper reviews the application of AI in the field of endoscopic detection of early EC, including squamous cell carcinoma and adenocarcinoma, and describes the relevant progress. Although up to now most of the studies evaluating the clinical application of AI in early EC endoscopic detection are focused on still images, AI-assisted real-time detection based on live-stream video may be the next step. Baishideng Publishing Group Inc 2021-04-14 2021-04-14 /pmc/articles/PMC8047537/ /pubmed/33911463 http://dx.doi.org/10.3748/wjg.v27.i14.1392 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 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 | Minireviews Liu, Yong Artificial intelligence-assisted endoscopic detection of esophageal neoplasia in early stage: The next step? |
title | Artificial intelligence-assisted endoscopic detection of esophageal neoplasia in early stage: The next step? |
title_full | Artificial intelligence-assisted endoscopic detection of esophageal neoplasia in early stage: The next step? |
title_fullStr | Artificial intelligence-assisted endoscopic detection of esophageal neoplasia in early stage: The next step? |
title_full_unstemmed | Artificial intelligence-assisted endoscopic detection of esophageal neoplasia in early stage: The next step? |
title_short | Artificial intelligence-assisted endoscopic detection of esophageal neoplasia in early stage: The next step? |
title_sort | artificial intelligence-assisted endoscopic detection of esophageal neoplasia in early stage: the next step? |
topic | Minireviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8047537/ https://www.ncbi.nlm.nih.gov/pubmed/33911463 http://dx.doi.org/10.3748/wjg.v27.i14.1392 |
work_keys_str_mv | AT liuyong artificialintelligenceassistedendoscopicdetectionofesophagealneoplasiainearlystagethenextstep |