Publication Name	World Journal of Gastroenterology
Manuscript ID	80202
Country	China

Received	2022-09-20 01:55
Peer-Review Started	2022-09-20 01:56
To Make the First Decision
Return for Revision	2022-10-18 21:53
Revised	2022-10-25 13:42
Second Decision	2022-11-14 03:27
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief	2022-11-17 17:45
Articles in Press	2022-11-17 17:45
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2022-11-23 10:13
Publish the Manuscript Online	2022-12-02 09:49

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/
Copyright	©The Author(s) 2022. 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	Deep learning based radiomics for gastrointestinal cancer diagnosis and treatment: A minireview
Manuscript Source	Invited Manuscript
All Author List	Pak Kin Wong, In Neng Chan, Hao-Ming Yan, Shan Gao, Chi Hong Wong, Tao Yan, Liang Yao, Ying Hu, Zhong-Ren Wang and Hon Ho Yu
Funding Agency and Grant Number	Funding Agency Grant Number Guangdong Basic and Applied Basic Research Fund, Shenzhen Joint Fund (Guangdong-Shenzhen Joint Fund) Guangdong-Hong Kong-Macau Research Team Project 2021B1515130003 The Science and Technology Development Fund of Macau 0026/2022/A Project of Xiangyang Science and Technology on Medical and Health Field 2022YL21
Corresponding Author	Tao Yan, PhD, Instructor, School of Mechanical Engineering, Hubei University of Arts and Science, No. 296 Longzhong Road, Xiangyang 441053, Hubei Province, China. yantao@hbuas.edu.cn
Key Words	Radiomics; Deep learning; Gastrointestinal cancer; Medical imaging
Core Tip	Radiomics, especially deep-learning-based radiomics (DLR), has revolutionized the diagnosis, assessment and prognosis of gastrointestinal (GI) cancer. This review provides an analysis and status of DLR in GI cancer and identifies future challenges and recommendations.
Publish Date	2022-12-02 09:49
Citation	Wong PK, Chan IN, Yan HM, Gao S, Wong CH, Yan T, Yao L, Hu Y, Wang ZR, Yu HH. Deep learning based radiomics for gastrointestinal cancer diagnosis and treatment: A minireview. World J Gastroenterol 2022; 28(45): 6363-6379
URL	https://www.wjgnet.com/1007-9327/full/v28/i45/6363.htm
DOI	https://dx.doi.org/10.3748/wjg.v28.i45.6363

Full Article (PDF)	WJG-28-6363.pdf
Full Article (Word)	WJG-28-6363.docx
Manuscript File	80202_Auto_Edited-LM.docx
Answering Reviewers	80202-Answering reviewers.pdf
Audio Core Tip	80202-Audio core tip.m4a
Conflict-of-Interest Disclosure Form	80202-Conflict-of-interest statement.pdf
Copyright License Agreement	80202-Copyright license agreement.pdf
Approved Grant Application Form(s) or Funding Agency Copy of any Approval Document(s)	80202-Grant application form(s).pdf
Non-Native Speakers of English Editing Certificate	80202-Language certificate.pdf
Peer-review Report	80202-Peer-review(s).pdf
Scientific Misconduct Check	80202-Bing-Chen YL-2.png
Scientific Editor Work List	80202-Scientific editor work list.pdf