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Publication Name World Journal of Gastroenterology
Manuscript ID 63514
Country/Territory United States
Category Mathematical and Computational Biology
Manuscript Type Minireviews
Article Title State of machine and deep learning in histopathological applications in digestive diseases
Manuscript Source Invited Manuscript
All Author List Soma Kobayashi, Joel H Saltz and Vincent W Yang
Funding Agency and Grant Number
Funding Agency Grant Number
National Institutes of Health GM008444
National Institutes of Health CA225021
National Institutes of Health DK052230
Corresponding Author Vincent W Yang, MD, PhD, Chairman, Full Professor, Department of Medicine, Renaissance School of Medicine, Stony Brook University, HSC T-16, Rm 040, 101 Nicolls Road, Stony Brook, NY 11794, United States. vincent.yang@stonybrookmedicine.edu
Key Words Artificial intelligence; Machine learning; Deep learning; Gastroenterology; Hepatology; Histopathology
Core Tip Machine learning- and deep learning-based imaging approaches have been increasingly applied to histopathological slides and hold much potential in areas spanning diagnosis, disease grading and characterizations, academic research, and clinical decision support mechanisms. As these studies have entered into translational applications, tracking the current state of these methodologies and the clinical areas in which impact is most likely is of high importance. This review will thus provide a background of major concepts and terminologies while highlighting emerging literature regarding histopathological applications of these techniques and challenges and opportunities moving forward.
Citation Kobayashi S, Saltz JH, Yang VW. State of machine and deep learning in histopathological applications in digestive diseases. World J Gastroenterol 2021; In press
2021-01-28 19:49
Peer-Review Started
2021-01-28 19:58
To Make the First Decision
Return for Revision
2021-02-24 05:11
2021-03-27 14:11
Second Decision
2021-04-29 08:43
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2021-04-29 11:33
Articles in Press
2021-04-29 11:33
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript
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/
Copyright © The Author(s) 2021. Published by Baishideng Publishing Group Inc. All rights reserved.
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
Assistant Editor Assistant Editor
Science Editor Chen-Chen Gao
Reviewer Code 05382551, and 05382551
Editorial Director
Journal Chief Editor
Company Chief Editor Jia-Ping Yan
Language Editor
Production Editor
Responsible Production Editor
Responsible Science Editor
Proofing Editorial Director Jin-Lei Wang
Proofing Editor-in-Chief Lian-Sheng Ma
Manuscript File 63514_Auto_Edited-JPY.docx
Answering Reviewers 63514-Answering reviewers.pdf
Audio Core Tip 63514-Audio core tip.m4a
Conflict-of-Interest Disclosure Form 63514-Conflict-of-interest statement.pdf
Copyright License Agreement 63514-Copyright license agreement.pdf
Approved Grant Application Form(s) or Funding Agency Copy of any Approval Document(s) 63514-Grant application form(s).pdf
Supplementary Material 63514-Copyright permission.pdf
Peer-review Report 63514-Peer-review(s).pdf
Scientific Misconduct Check 63514-Bing-Wang JL-1.jpg
Scientific Misconduct Check 63514-Scientific misconduct check.pdf
Scientific Editor Work List 63514-Scientific editor work list.pdf