Publication Name	World Journal of Gastroenterology
Manuscript ID	80458
Country	Spain

Received	2022-09-28 10:32
Peer-Review Started	2022-09-28 10:34
To Make the First Decision
Return for Revision	2023-01-03 21:08
Revised	2023-01-13 17:45
Second Decision	2023-02-07 04:04
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2023-02-27 22:39
Articles in Press	2023-02-27 22:39
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2023-02-28 07:09
Publish the Manuscript Online	2023-03-07 16:31

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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Website	http://www.wjgnet.com

Category	Gastroenterology & Hepatology
Manuscript Type	Review
Article Title	Clinical impact of artificial intelligence-based solutions on imaging of the pancreas and liver
Manuscript Source	Invited Manuscript
All Author List	M Alvaro Berbís, Felix Paulano Godino, Javier Royuela del Val, Lidia Alcalá Mata and Antonio Luna
Funding Agency and Grant Number
Corresponding Author	Antonio Luna, MD, PhD, Director, Director, Department of Radiology, HT Médica, Clínica las Nieves, MRI Unit, 2 Carmelo Torres, Jaén 23007, Spain. aluna70@htmedica.com
Key Words	Artificial intelligence; Machine learning; Deep learning; Imaging; Liver; Pancreas
Core Tip	The gastroenterology field is changing with the application of artificial intelligence (AI) solutions capable of assisting and even automating the interpretation of radiological images (ultrasound, endoscopic ultrasound, computerized tomography, magnetic resonance imaging, and positron emission tomography), generating accurate and reproducible diagnoses. AI can further be applied to other steps of the radiological workflow beyond image interpretation, including test selection, image quality improvement, acceleration of image acquisition, and prediction of patient prognosis and outcome. We herein discuss the current evidence, challenges, and future directions on the application of AI to hepatic and pancreatic radiology.
Publish Date	2023-03-07 16:31
Citation	Berbís MA, Paulano Godino F, Royuela del Val J, Alcalá Mata L, Luna A. Clinical impact of artificial intelligence-based solutions on imaging of the pancreas and liver. World J Gastroenterol 2023; 29(9): 1427-1445
URL	https://www.wjgnet.com/1007-9327/full/v29/i9/1427.htm
DOI	https://dx.doi.org/10.3748/wjg.v29.i9.1427

Full Article (PDF)	WJG-29-1427.pdf
Full Article (Word)	WJG-29-1427.docx
Manuscript File	80458_Auto_Edited-LM.docx
Answering Reviewers	80458-Answering reviewers.pdf
Audio Core Tip	80458-Audio core tip.mp3
Conflict-of-Interest Disclosure Form	80458-Conflict-of-interest statement.pdf
Copyright License Agreement	80458-Copyright license agreement.pdf
Non-Native Speakers of English Editing Certificate	80458-Language certificate.pdf
Peer-review Report	80458-Peer-review(s).pdf
Scientific Misconduct Check	80458-Bing-Chen YL-2.png
Scientific Editor Work List	80458-Scientific editor work list.pdf
CrossCheck Report	80458-CrossCheck report.pdf