Publication Name	Artificial Intelligence in Gastroenterology
Manuscript ID	75504
Country	United States

Received	2022-02-01 02:20
Peer-Review Started	2022-02-01 02:21
To Make the First Decision
Return for Revision	2022-02-18 07:35
Revised	2022-03-28 04:25
Second Decision	2022-04-15 01:58
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief	2022-04-19 21:42
Articles in Press	2022-04-19 21:42
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2022-04-20 03:27
Publish the Manuscript Online	2022-04-29 11:12

ISSN	2644-3236 (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: http://creativecommons.org/licenses/by-nc/4.0/
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Category	Gastroenterology & Hepatology
Manuscript Type	Minireviews
Article Title	Machine learning in endoscopic ultrasonography and the pancreas: The new frontier?
Manuscript Source	Invited Manuscript
All Author List	Cem Simsek and Linda S Lee
Funding Agency and Grant Number
Corresponding Author	Linda S Lee, MD, Associate Professor, Division of Gastroenterology, Hepatology and Endoscopy, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Division of Gastroenterology, Hepatology, and Endoscopy, Brigham and Women's Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115, USA. lslee@partners.org, Boston, MA 02115, United States. lslee@partners.org
Key Words	Artificial intelligence; Pancreas; Endoscopic ultrasonography; Pancreatic cancer; Autoimmune pancreatitis; Pancreatic cystic lesions
Core Tip	Several reviews in the literature have discussed the use of artificial intelligence in pancreatic disease. However, this is the first review that focuses on the application of artificial intelligence (AI) specifically to endoscopic ultrasonography (EUS) of the pancreas, including pancreatic cystic lesions, pancreatic cancer, chronic pancreatitis, and autoimmune pancreatitis, where it appears to enhance EUS diagnosis. AI may also offer real-time assistance during procedures to direct biopsy towards the highest yield areas as well augment EUS training.
Publish Date	2022-04-29 11:12
Citation	Simsek C, Lee LS. Machine learning in endoscopic ultrasonography and the pancreas: The new frontier? Artif Intell Gastroenterol 2022; 3(2): 54-65
URL	https://www.wjgnet.com/2644-3236/full/v3/i2/54.htm
DOI	https://dx.doi.org/10.35712/aig.v3.i2.54

Full Article (PDF)	AIG-3-54.pdf
Full Article (Word)	AIG-3-54.docx
Manuscript File	75504_Auto_Edited-LJH.docx
Answering Reviewers	75504-Answering reviewers.pdf
Audio Core Tip	75504-Audio core tip.m4a
Conflict-of-Interest Disclosure Form	75504-Conflict-of-interest statement.pdf
Copyright License Agreement	75504-Copyright license agreement.pdf
Peer-review Report	75504-Peer-review(s).pdf
Scientific Misconduct Check	75504-Bing-Liu JH-2.jpg
Scientific Misconduct Check	75504-CrossCheck.jpg
Scientific Editor Work List	75504-Scientific editor work list.pdf