Publication Name	World Journal of Gastroenterology
Manuscript ID	62186
Country	United States

Received	2020-12-31 18:33
Peer-Review Started	2020-12-31 18:34
To Make the First Decision
Return for Revision	2021-01-17 00:25
Revised	2021-01-22 22:52
Second Decision	2021-03-12 14:19
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief	2021-03-13 06:47
Articles in Press	2021-03-13 06:47
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2021-03-29 01:47
Publish the Manuscript Online	2021-03-30 07:03

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: http://creativecommons.org/Licenses/by-nc/4.0/
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Category	Gastroenterology & Hepatology
Manuscript Type	Minireviews
Article Title	Artificial intelligence for early detection of pancreatic adenocarcinoma: The future is promising
Manuscript Source	Invited Manuscript
All Author List	Antonio Mendoza Ladd and David L Diehl
ORCID	Author(s) ORCID Number Antonio Mendoza Ladd http://orcid.org/0000-0002-8013-3545 David L Diehl http://orcid.org/0000-0003-4128-3839
Funding Agency and Grant Number
Corresponding Author	Antonio Mendoza Ladd, FACG, FASGE, Assistant Professor, Internal Medicine, Division of Gastroenterology, Texas Tech University Health Sciences Center El Paso, 4800 Alberta Avenue, El Paso, TX 79905, United States. dr_ladd25@yahoo.com
Key Words	Pancreatic adenocarcinoma; Artificial intelligence; Neural network; Future perspectives; Early diagnosis; Improved performance
Core Tip	Pancreatic adenocarcinoma is one of the deadliest malignancies in the world. Several factors are responsible for this but delayed diagnosis is one of the most important. Despite improvements in diagnostic methods, patients with early lesions are still missed in clinical practice. Artificial intelligence-assisted diagnostic methods have the potential of improving the clinical outcomes of these patients. However, major improvements in artificial intelligence technology and its implementation need to occur before potential benefits can be attained.
Publish Date	2021-03-30 07:03
Citation	Mendoza Ladd A, Diehl D. Artificial intelligence for early detection of pancreatic adenocarcinoma: The future is promising. World J Gastroenterol 2021; 27(13): 1283-1295
URL	https://www.wjgnet.com/1007-9327/full/v27/i13/1283.htm
DOI	https://dx.doi.org/10.3748/wjg.v27.i13.1283

Full Article (PDF)	WJG-27-1283.pdf
Full Article (Word)	WJG-27-1283.docx
Manuscript File	62186_Auto_Edited.docx
Answering Reviewers	62186-Answering reviewers.pdf
Audio Core Tip	62186-Audio core tip.m4a
Conflict-of-Interest Disclosure Form	62186-Conflict-of-interest statement.pdf
Copyright License Agreement	62186-Copyright license agreement.pdf
Peer-review Report	62186-Peer-review(s).pdf
Scientific Misconduct Check	62186-Bing-Wang JL-1.jpg
Scientific Misconduct Check	62186-Scientific misconduct check.pdf
Scientific Editor Work List	62186-Scientific editor work list.pdf