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Articles Published Processes
9/29/2020 5:02:15 AM | Browse: 898 | Download: 1618
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Received |
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2020-06-29 19:38 |
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Peer-Review Started |
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2020-06-29 19:38 |
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To Make the First Decision |
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Return for Revision |
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2020-08-01 07:23 |
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Revised |
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2020-09-25 15:19 |
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Second Decision |
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2020-09-27 01:30 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2020-09-27 01:58 |
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Articles in Press |
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2020-09-27 01:58 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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2020-09-28 16:48 |
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Typeset the Manuscript |
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2020-09-29 02:35 |
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Publish the Manuscript Online |
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2020-09-29 05:02 |
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) 2020. Published by Baishideng Publishing Group Inc. All rights reserved. |
Article Reprints |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/247
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Permissions |
For details, please visit: http://www.wjgnet.com/bpg/gerinfo/207
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Publisher |
Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA |
Website |
http://www.wjgnet.com |
Category |
Oncology |
Manuscript Type |
Minireviews |
Article Title |
Artificial intelligence for the study of colorectal cancer tissue slides
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Manuscript Source |
Invited Manuscript |
All Author List |
Vincenzo Formica, Cristina Morelli, Silvia Riondino, Nicola Renzi, Daniele Nitti and Mario Roselli |
ORCID |
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Funding Agency and Grant Number |
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Corresponding Author |
Vincenzo Formica, MD, PhD, Chief Doctor, Department of Systems Medicine, Medical Oncology Unit, Tor Vergata University Hospital, Viale Oxford 81, Rome 00133, Italy. vincenzo.formica@uniroma2.it |
Key Words |
Artificial intelligence; Colorectal cancer; Digital pathology; Deep learning; Machine learning; Tumor-infiltrating lymphocytes |
Core Tip |
Artificial intelligence (AI) is incredibly gaining momentum as companion diagnostic in a number of fields in oncology. In the present mini-review we summarize main uses and findings of AI applied to the analysis of digital histopathological images of slides from colorectal cancer patients. |
Publish Date |
2020-09-29 05:02 |
Citation |
Formica V, Morelli C, Riondino S, Renzi N, Nitti D, Roselli M. Artificial intelligence for the study of colorectal cancer tissue slides. Artif Intell Gastroenterol 2020; 1(3): 51-59 |
URL |
https://www.wjgnet.com/2644-3236/full/v1/i3/51.htm |
DOI |
https://dx.doi.org/10.35712/aig.v1.i3.51 |
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