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7/5/2021 6:42:12 AM | Browse: 377 | Download: 691
Publication Name Artificial Intelligence in Gastroenterology
Manuscript ID 63530
Country/Territory 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 Company 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.
Article Reprints For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
Permissions For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
Publisher Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA
Website http://www.wjgnet.com
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
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