Publication Name	World Journal of Gastroenterology
Manuscript ID	66595
Country	Japan

Received	2021-04-03 07:38
Peer-Review Started	2021-04-03 07:41
To Make the First Decision
Return for Revision	2021-07-03 02:26
Revised	2021-08-02 03:14
Second Decision	2021-11-15 03:34
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2021-11-15 07:01
Articles in Press	2021-11-15 07:01
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2021-11-16 15:16
Publish the Manuscript Online	2021-11-19 11:15

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	Minireviews
Article Title	Recent advances in artificial intelligence for pancreatic ductal adenocarcinoma
Manuscript Source	Invited Manuscript
All Author List	Hiromitsu Hayashi, Norio Uemura, Kazuki Matsumura, Liu Zhao, Hiroki Sato, Yuta Shiraishi, Yo-ichi Yamashita and Hideo Baba
Funding Agency and Grant Number
Corresponding Author	Hiromitsu Hayashi, FACS, MD, PhD, Associate Professor, Department of Gastroenterological Surgery, Graduate School of Life Sciences, Kumamoto University, 1-1-1 Honjo, Chuo-ku, Kumamoto 860-8556, Japan. hhayasi@kumamoto-u.ac.jp
Key Words	Pancreatic cancer; Pancreatic ductal adenocarcinoma; Artificial intelligence; Machine learning; Precision medicine
Core Tip	Pancreatic ductal adenocarcinoma (PDAC) remains the most lethal type of cancer. Artificial intelligence (AI) is the ability of a machine to learn and display intelligence to solve problems. AI can help to transform big data into clinically actionable insights more efficiently, reduce inevitable errors to improve diagnostic accuracy, and make real-time predictions. AI-based omics analyses should be the next alternative approach to improve survival outcomes in PDAC by discovering biomarkers for early detection, molecular/genomic subtyping, treatment guidance, and predicting recurrence and survival. The present review mainly focuses on recent advances of AI in PDAC for clinicians.
Publish Date	2021-11-19 11:15
Citation	Hayashi H, Uemura N, Matsumura K, Zhao L, Sato H, Shiraishi Y, Yamashita YI, Baba H. Recent advances in artificial intelligence for pancreatic ductal adenocarcinoma. World J Gastroenterol 2021; 27(43): 7480-7496
URL	https://www.wjgnet.com/1007-9327/full/v27/i43/7480.htm
DOI	https://dx.doi.org/10.3748/wjg.v27.i43.7480

Full Article (PDF)	WJG-27-7480.pdf
Full Article (Word)	WJG-27-7480.docx
Manuscript File	66595_Auto_Edited.docx
Answering Reviewers	66595-Answering reviewers.pdf
Audio Core Tip	66595-Audio core tip.mp3
Conflict-of-Interest Disclosure Form	66595-Conflict-of-interest statement.pdf
Copyright License Agreement	66595-Copyright license agreement.pdf
Non-Native Speakers of English Editing Certificate	66595-Language certificate.pdf
Supplementary Material	66595-Supplementary material.pdf
Peer-review Report	66595-Peer-review(s).pdf
Scientific Editor Work List	66595-Scientific editor work list.pdf
CrossCheck Report	66595-CrossCheck report.pdf