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Publication Name Artificial Intelligence in Gastroenterology
Manuscript ID 57853
Country Italy
Category Oncology
Manuscript Type Minireviews
Article Title Artificial intelligence for the study of colorectal cancer tissue slides
Manuscript Source Invited Manuscript
All Author List Vincenzo Formica, Cristina Morelli, Silvia Riondino, Nicola Renzi, Daniele Nitti and Mario Roselli
Funding Agency and Grant Number
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.
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
Received
2020-06-29 19:38
Peer-Review Started
2020-06-29 19:38
To Make the First Decision
Return for Revision
2020-08-01 07:23
Revised
2020-09-25 15:19
Second Decision
2020-09-27 01:30
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2020-09-27 01:58
Articles in Press
2020-09-27 01:58
Publication Fee Transferred
Edit the Manuscript by Language Editor
2020-09-28 16:48
Typeset the Manuscript
2020-09-29 02:35
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.
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