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Articles Published Processes
9/7/2023 8:44:38 AM | Browse: 236 | Download: 511
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Received |
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2023-06-03 17:08 |
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Peer-Review Started |
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2023-06-03 17:10 |
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To Make the First Decision |
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Return for Revision |
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2023-07-04 03:52 |
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Revised |
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2023-07-24 19:23 |
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Second Decision |
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2023-08-07 02:53 |
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Accepted by Journal Editor-in-Chief |
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Accepted by Executive Editor-in-Chief |
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2023-08-07 08:08 |
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Articles in Press |
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2023-08-07 08:08 |
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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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2023-09-05 05:57 |
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Publish the Manuscript Online |
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2023-09-07 08:44 |
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) 2023. 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 |
Engineering, Biomedical |
Manuscript Type |
Evidence Review |
Article Title |
Artificial intelligence in the diagnosis of thyroid cancer: Recent advances and future directions
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Manuscript Source |
Invited Manuscript |
All Author List |
Lakshmi Nagendra, Joseph M Pappachan and Cornelius James Fernandez |
ORCID |
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Funding Agency and Grant Number |
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Corresponding Author |
Joseph M Pappachan, FRCP, MD, Academic Editor, Professor, Senior Researcher, Department of Endocrinology & Metabolism, Lancashire Teaching Hospitals NHS Trust, Sharoe Green Lane, Preston PR2 9HT, United Kingdom. drpappachan@yahoo.co.in |
Key Words |
Artificial intelligence; Thyroid cancer; Deep learning models; Histopathology; Thyroid ultrasound |
Core Tip |
In its broadest sense artificial intelligence (AI) is the ability of machines to approach problem-solving with human-like logic. Thyroid cancer is the most common endocrine malignancy with increasing incidence rates, but with stable lower mortality rates. As in the other domains of healthcare, AI is now revolutionising the diagnosis, management, and prognostication of thyroid cancer. In this evidence-based review we update the recent advances in AI-based techniques for the management of thyroid cancer. |
Publish Date |
2023-09-07 08:44 |
Citation |
Nagendra L, Pappachan JM, Fernandez CJ. Artificial intelligence in the diagnosis of thyroid cancer: Recent advances and future directions. Artif Intell Cancer 2023; 4(1): 1-10 |
URL |
https://www.wjgnet.com/2644-3228/full/v4/i1/1.htm |
DOI |
https://dx.doi.org/10.35713/aic.v4.i1.1 |
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