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6/28/2022 1:19:02 PM | Browse: 231 | Download: 430
Publication Name World Journal of Radiology
Manuscript ID 75501
Country/Territory Türkiye
Received
2022-01-31 21:15
Peer-Review Started
2022-01-31 21:17
To Make the First Decision
Return for Revision
2022-04-08 08:47
Revised
2022-04-20 16:43
Second Decision
2022-06-06 03:23
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief
2022-06-17 22:58
Articles in Press
2022-06-17 22:58
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript
2022-06-22 09:08
Publish the Manuscript Online
2022-06-28 13:12
ISSN 1949-8470 (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) 2022. 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 Radiology, Nuclear Medicine & Medical Imaging
Manuscript Type Minireviews
Article Title Artificial intelligence technologies in nuclear medicine
Manuscript Source Invited Manuscript
All Author List Muge Oner Tamam and Muhlis Can Tamam
Funding Agency and Grant Number
Corresponding Author Muge Oner Tamam, MD, Associate Professor, Nuclear Medicine, Tamam, MO (reprint author), Prof. Dr. Cemil Tascioglu City Hospital, Istanbul, Turkey., Darulaceze cad., İstanbul 34381, Türkiye. mugeoner@yahoo.com
Key Words Artificial intelligence; Machine learning; Deep learning; Artificial neural networks; Convolutional neural networks; Generative adversarial networks
Core Tip Artificial intelligence is a distinguished tool for creating tailor-made medicine. Artificial intelligence (AI) consists of machine learning, deep learning, artificial neural networks, convolutional neural networks, and generative adversarial networks. These AI applications affect all phases of a routine medical imaging workflow in nuclear medicine: planning, image acquisition, and interpretation. The integration of AI into clinical workflow and protocols of medical imaging will provide the opportunity to decrease the error rate of physicians and eventually lead to improved patient management.
Publish Date 2022-06-28 13:12
Citation Tamam MO, Tamam MC. Artificial intelligence technologies in nuclear medicine. World J Radiol 2022; 14(6): 151-154
URL https://www.wjgnet.com/1949-8470/full/v14/i6/151.htm
DOI https://dx.doi.org/10.4329/wjr.v14.i6.151
Full Article (PDF) WJR-14-151.pdf
Full Article (Word) WJR-14-151.docx
Manuscript File 75501_Auto_Edited-LJH-LS.docx
Answering Reviewers 75501-Answering reviewers.pdf
Audio Core Tip 75501-Audio core tip.m4a
Conflict-of-Interest Disclosure Form 75501-Conflict-of-interest statement.pdf
Copyright License Agreement 75501-Copyright license agreement.pdf
Non-Native Speakers of English Editing Certificate 75501-Language certificate.pdf
Peer-review Report 75501-Peer-review(s).pdf
Scientific Misconduct Check 75501-Bing-Liu JH-2.jpg
Scientific Misconduct Check 75501-CrossCheck.jpg
Scientific Editor Work List 75501-Scientific editor work list.pdf