Publication Name	Artificial Intelligence in Gastroenterology
Manuscript ID	63530
Country	Ireland

Received	2021-01-28 23:47
Peer-Review Started	2021-01-29 02:41
To Make the First Decision
Return for Revision	2021-05-04 12:09
Revised	2021-05-21 16:15
Second Decision	2021-06-18 08:56
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2021-06-18 11:32
Articles in Press	2021-06-18 11:32
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2021-06-23 09:21
Publish the Manuscript Online	2021-07-05 06:25

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/
Copyright	© The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
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Category	Gastroenterology & Hepatology
Manuscript Type	Minireviews
Article Title	Biophysics inspired artificial intelligence for colorectal cancer characterization
Manuscript Source	Invited Manuscript
All Author List	Niall P Hardy, Jeffrey Dalli, Pól Mac Aonghusa, Peter M Neary and Ronan A Cahill
ORCID	Author(s) ORCID Number Niall P Hardy http://orcid.org/0000-0002-7036-3910 Jeffrey Dalli http://orcid.org/0001-0001-0001-0001 Pól Mac Aonghusa http://orcid.org/0001-0001-0001-0002 Peter M Neary http://orcid.org/0000-0002-9319-286X Ronan A Cahill http://orcid.org/0000-0002-1270-4000
Funding Agency and Grant Number
Corresponding Author	Ronan A Cahill, FRCS, MBChB, MD, Professor, Department of Surgery, Mater Misericordiae University Hospital (MMUH), 47 Eccles Street, Dublin 7, Ireland. ronan.cahill@ucd.ie
Key Words	Gastroenterology; Artificial intelligence; Gastrointestinal surgery; Deep learning; Biophysics; Machine learning
Core Tip	In this piece we provide an overview of current state of the art in gastroenterology and gastrointestinal surgery. We discuss current deep learning artificial intelligence methods for colorectal lesion detection and characterization as well as exploring biophysics inspired artificial intelligence methods and the potential role they can play in the future of gastroenterological practice.
Publish Date	2021-07-05 06:25
Citation	Hardy NP, Dalli J, Mac Aonghusa P, Neary PM, Cahill RA. Biophysics inspired artificial intelligence for colorectal cancer characterization. Artif Intell Gastroenterol 2021; 2(3): 77-84
URL	https://www.wjgnet.com/2644-3236/full/v2/i3/77.htm
DOI	https://dx.doi.org/10.35712/aig.v2.i3.77

Full Article (PDF)	AIG-2-77.pdf
Full Article (Word)	AIG-2-77.docx
Manuscript File	63530_Auto_Edited-JPY.docx
Answering Reviewers	63530-Answering reviewers.pdf
Audio Core Tip	63530-Audio core tip.m4a
Conflict-of-Interest Disclosure Form	63530-Conflict-of-interest statement.pdf
Copyright License Agreement	63530-Copyright license agreement.pdf
Peer-review Report	63530-Peer-review(s).pdf
Scientific Misconduct Check	63530-Bing-Wang JL-1.jpg
Scientific Misconduct Check	63530-Scientific misconduct check.pdf
Scientific Editor Work List	63530-Scientific editor work list.pdf
CrossCheck Report	63530-CrossCheck report.pdf