Copyright
©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Radiol. Mar 28, 2022; 14(3): 55-59
Published online Mar 28, 2022. doi: 10.4329/wjr.v14.i3.55
Published online Mar 28, 2022. doi: 10.4329/wjr.v14.i3.55
Artificial intelligence in dentomaxillofacial radiology
Seyide Tugce Gokdeniz, Kıvanç Kamburoğlu, Department of Dentomaxillofacial Radiology, Ankara University Faculty of Dentistry, Ankara 06500, Turkey
Author contributions: Gökdeniz ST and Kamburoğlu K have made substantial contributions to conception and writing of the paper and revising it critically for important intellectual content; both have approved the final version to be published and assume full responsibility for its content; all authors have agreed to the order of authorship prior to submission.
Conflict-of-interest statement: Authors declare no conflict of interests for this article.
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: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Kıvanç Kamburoğlu, DDS, MSc, PhD, Professor, Department of Dentomaxillofacial Radiology, Ankara University Faculty of Dentistry, Besevler, Ankara 06500, Turkey. dtkivo@yahoo.com
Received: March 20, 2021
Peer-review started: March 20, 2021
First decision: July 18, 2021
Revised: September 5, 2021
Accepted: February 22, 2022
Article in press: February 22, 2022
Published online: March 28, 2022
Processing time: 369 Days and 23.5 Hours
Peer-review started: March 20, 2021
First decision: July 18, 2021
Revised: September 5, 2021
Accepted: February 22, 2022
Article in press: February 22, 2022
Published online: March 28, 2022
Processing time: 369 Days and 23.5 Hours
Core Tip
Core Tip: Scientists are enthusiastic about conducting artificial intelligence (AI) research related to dentomaxillofacial radiology (DMFR). Image and patient recognition are important in DMFR, however initial investment costs are still high and misdiagnosis may occur in real clinical situations. Up until now, DMFR related AI studies revealed successful results to some extent, however human physiological system is so complex that AI can be a supplementary method but not a substitution for human knowledge, capability and decision-making ability.