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11/30/2020 5:58:12 AM | Browse: 473 | Download: 760
Publication Name Artificial Intelligence in Cancer
Manuscript ID 59750
Country Spain
Received
2020-09-26 10:41
Peer-Review Started
2020-09-26 10:42
To Make the First Decision
Return for Revision
2020-10-22 03:49
Revised
2020-11-05 16:47
Second Decision
2020-11-17 12:44
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2020-11-21 06:00
Articles in Press
2020-11-21 06:00
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript
2020-11-29 12:47
Publish the Manuscript Online
2020-11-30 05:58
ISSN 2644-3228 (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) 2020. 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 Cell Biology
Manuscript Type Minireviews
Article Title Artificial intelligence for modeling uveal melanoma
Manuscript Source Invited Manuscript
All Author List Beatriz Santos-Buitrago, Gustavo Santos-García and Emiliano Hernández-Galilea
ORCID
Author(s) ORCID Number
Beatriz Santos-Buitrago http://orcid.org/0000-0001-6609-5494
Gustavo Santos-García http://orcid.org/0000-0001-6609-5493
Emiliano Hernández-Galilea http://orcid.org/0000-0001-6609-5495
Funding Agency and Grant Number
Corresponding Author Gustavo Santos-García, PhD, Professor, IME, University of Salamanca, FES Building, Campus Miguel de Unamuno, Salamanca 37007, Spain. santos@usal.es
Key Words Uveal melanoma; Signal transduction; Pathway Logic; Symbolic systems biology; Artificial intelligence;
Core Tip Artificial intelligence offers rule-based models that favor the understanding of cell biology (signaling pathways) involved in the uveal melanoma.
Publish Date 2020-11-30 05:58
Citation Santos-Buitrago B, Santos-García G, Hernández-Galilea E. Artificial intelligence for modeling uveal melanoma. Artif Intell Cancer 2020; 1(4): 51-65
URL https://www.wjgnet.com/2644-3228/full/v1/i4/51.htm
DOI https://dx.doi.org/10.35713/aic.v1.i4.51
Full Article (PDF) AIC-1-51.pdf
Full Article (Word) AIC-1-51.docx
Manuscript File 59750_Auto_Edited.docx
Answering Reviewers 59750-Answering reviewers.pdf
Audio Core Tip 59750-Audio core tip.m4a
Conflict-of-Interest Disclosure Form 59750-Conflict-of-interest statement.pdf
Copyright License Agreement 59750-Copyright license agreement.pdf
Peer-review Report 59750-Peer-review(s).pdf
Scientific Misconduct Check 59750-Scientific misconduct check.pdf
Scientific Editor Work List 59750-Scientific editor work list.pdf