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3/8/2021 11:20:03 AM | Browse: 242 | Download: 315
Publication Name World Journal of Translational Medicine
Manuscript ID 60193
Country/Territory United States
2020-10-19 18:32
Peer-Review Started
2020-10-19 18:32
To Make the First Decision
Return for Revision
2020-11-16 22:05
2020-12-22 05:05
Second Decision
2021-02-26 07:50
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2021-03-02 03:17
Articles in Press
2021-03-02 03:17
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript
2021-03-08 02:31
Publish the Manuscript Online
2021-03-08 11:20
ISSN 2220-6132 (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 Oncology
Manuscript Type Editorial
Article Title Machine intelligence for precision oncology
Manuscript Source Invited Manuscript
All Author List Nelson S Yee
Author(s) ORCID Number
Nelson S Yee http://orcid.org/0000-0002-1457-9047
Funding Agency and Grant Number
Corresponding Author Nelson S Yee, BPharm, FACP, MD, PhD, Associate Professor, Attending Doctor, Department of Medicine, The Pennsylvania State University College of Medicine, Penn State Cancer Institute, Penn State Health Milton S. Hershey Medical Center, 500 University Drive, Hershey, PA 17033-0850, United States. nyee@pennstatehealth.psu.edu
Key Words Artificial intelligence; Deep learning; Machine learning; Precision oncology; Radiomics; Radiogenomics
Core Tip Artificial intelligence represents the future of healthcare particularly precision oncology for prevention, detection, risk assessment, and treatment of cancer. Application of machine learning- and deep learning-based algorithms in translational research has been demonstrated to improve accuracy of cancer diagnosis and anti-cancer drug development. Multi-disciplinary collaboration with resolution of ethical and regulatory issues of multi-modal machine intelligence are indicated for implementation of computer-assisted clinical decision on individualized patient management.
Publish Date 2021-03-08 11:20
Citation Yee NS. Machine intelligence for precision oncology. World J Transl Med 2021; 9(1): 1-10
URL https://www.wjgnet.com/2220-6132/full/v9/i1/1.htm
DOI https://dx.doi.org/10.5528/wjtm.v9.i1.1
Full Article (PDF) WJTM-9-1.pdf
Full Article (Word) WJTM-9-1.docx
Manuscript File 60193_Auto_Edited_LM.docx
Answering Reviewers 60193-Answering reviewers.pdf
Audio Core Tip 60193-Audio core tip.mp3
Conflict-of-Interest Disclosure Form 60193-Conflict-of-interest statement.pdf
Copyright License Agreement 60193-Copyright license agreement.pdf
Peer-review Report 60193-Peer-review(s).pdf
Scientific Misconduct Check 60193-Scientific misconduct check.pdf
Scientific Editor Work List 60193-Scientific editor work list.pdf