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Articles Published Processes
5/20/2021 8:38:05 AM | Browse: 469 | Download: 1165
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Received |
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2021-01-28 19:49 |
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Peer-Review Started |
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2021-01-28 19:58 |
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To Make the First Decision |
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Return for Revision |
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2021-02-24 05:11 |
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Revised |
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2021-03-27 14:11 |
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Second Decision |
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2021-04-29 08:43 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2021-04-29 11:33 |
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Articles in Press |
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2021-04-29 11:33 |
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Publication Fee Transferred |
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Edit the Manuscript by Language Editor |
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Typeset the Manuscript |
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2021-05-18 08:23 |
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Publish the Manuscript Online |
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2021-05-20 08:38 |
| 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: 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
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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 |
Mathematical & Computational Biology |
| Manuscript Type |
Minireviews |
| Article Title |
State of machine and deep learning in histopathological applications in digestive diseases
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| Manuscript Source |
Invited Manuscript |
| All Author List |
Soma Kobayashi, Joel H Saltz and Vincent W Yang |
| ORCID |
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| Funding Agency and Grant Number |
| Funding Agency |
Grant Number |
| National Institutes of Health |
GM008444 |
| National Institutes of Health |
CA225021 |
| National Institutes of Health |
DK052230 |
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| Corresponding Author |
Vincent W Yang, MD, PhD, Chairman, Full Professor, Department of Medicine, Renaissance School of Medicine, Stony Brook University, HSC T-16, Rm 040, 101 Nicolls Road, Stony Brook, NY 11794, United States. vincent.yang@stonybrookmedicine.edu |
| Key Words |
Artificial intelligence; Machine learning; Deep learning; Gastroenterology; Hepatology; Histopathology |
| Core Tip |
Machine learning- and deep learning-based imaging approaches have been increasingly applied to histopathological slides and hold much potential in areas spanning diagnosis, disease grading and characterizations, academic research, and clinical decision support mechanisms. As these studies have entered into translational applications, tracking the current state of these methodologies and the clinical areas in which impact is most likely is of high importance. This review will thus provide a background of major concepts and terminologies while highlighting emerging literature regarding histopathological applications of these techniques and challenges and opportunities moving forward. |
| Publish Date |
2021-05-20 08:38 |
| Citation |
Kobayashi S, Saltz JH, Yang VW. State of machine and deep learning in histopathological applications in digestive diseases. World J Gastroenterol 2021; 27(20): 2545-2575 |
| URL |
https://www.wjgnet.com/1007-9327/full/v27/i20/2545.htm |
| DOI |
https://dx.doi.org/10.3748/wjg.v27.i20.2545 |
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