Publication Name	World Journal of Gastroenterology
Manuscript ID	91852
Country	Italy

Received	2024-01-07 10:50
Peer-Review Started	2024-01-07 10:50
To Make the First Decision
Return for Revision	2024-01-23 02:14
Revised	2024-01-27 09:48
Second Decision	2024-02-27 03:20
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief	2024-02-27 06:01
Articles in Press	2024-02-27 06:01
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2024-03-04 08:52
Publish the Manuscript Online	2024-03-21 11:37

ISSN	1007-9327 (print) and 2219-2840 (online)
Open Access	This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (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. See: https://creativecommons.org/Licenses/by-nc/4.0/
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Category	Gastroenterology & Hepatology
Manuscript Type	Editorial
Article Title	Advancements in Barrett's esophagus detection: The role of artificial intelligence and its implications
Manuscript Source	Invited Manuscript
All Author List	Sara Massironi
Funding Agency and Grant Number
Corresponding Author	Sara Massironi, MD, PhD, Adjunct Professor, Division of Gastroenterology and Center for Autoimmune Liver Diseases, Department of Medicine and Surgery, Fondazione IRCCS San Gerardo dei Tintori, University of Milano-Bicocca, Via Pergolesi 33, Monza 20900, Italy. sara.massironi@libero.it
Key Words	Barrett's esophagus; Artificial intelligence; Endoscopic images; Artificial intelligence model; Early cancer detection; Endoscopy
Core Tip	The use of artificial intelligence (AI) to detect Barrett's esophagus (BE) is a groundbreaking advancement in the field of gastroenterology. This innovative approach, which employs endoscopic images for training AI models, challenges the conventional distinction between endoscopic and histological BE. The results show good promise, with the AI system achieving high accuracy, sensitivity, and specificity in BE detection. This development has the potential to reduce unnecessary biopsies and streamline the diagnostic process. However, the adaptability of AI to different endoscopic systems remains a critical consideration, warranting further research for widespread clinical implementation.
Publish Date	2024-03-21 11:37
Citation	Massironi S. Advancements in Barrett's esophagus detection: The role of artificial intelligence and its implications. World J Gastroenterol 2024; 30(11): 1494-1496
URL	https://www.wjgnet.com/1007-9327/full/v30/i11/1494.htm
DOI	https://dx.doi.org/10.3748/wjg.v30.i11.1494

Full Article (PDF)	WJG-30-1494-with-cover.pdf
Manuscript File	91852_Auto_Edited-YJP.docx
Answering Reviewers	91852-Answering reviewers.pdf
Audio Core Tip	91852-Audio core tip.m4a
Conflict-of-Interest Disclosure Form	91852-Conflict-of-interest statement.pdf
Copyright License Agreement	91852-Copyright license agreement.pdf
Non-Native Speakers of English Editing Certificate	91852-Language certificate.pdf
Peer-review Report	91852-Peer-review(s).pdf
Scientific Misconduct Check	91852-Bing-Lin C-2.png
Scientific Editor Work List	91852-Scientific editor work list.pdf