Publication Name	Artificial Intelligence in Medical Imaging
Manuscript ID	73882
Country	China

Received	2021-12-07 08:09
Peer-Review Started	2021-12-07 08:10
To Make the First Decision
Return for Revision	2021-12-13 02:12
Revised	2021-12-20 03:17
Second Decision	2021-12-28 06:18
Accepted by Journal Editor-in-Chief
Accepted by Company Editor-in-Chief	2021-12-28 07:31
Articles in Press	2021-12-28 07:31
Publication Fee Transferred
Edit the Manuscript by Language Editor	2021-12-23 10:38
Typeset the Manuscript	2021-12-28 08:36
Publish the Manuscript Online	2021-12-28 12:39

ISSN	2644-3260 (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.
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Category	Dentistry, Oral Surgery & Medicine
Manuscript Type	Minireviews
Article Title	Application of machine learning in oral and maxillofacial surgery
Manuscript Source	Invited Manuscript
All Author List	Kai-Xin Yan, Lei Liu and Hui Li
Funding Agency and Grant Number
Corresponding Author	Hui Li, MD, PhD, Assistant Professor, State Key Laboratory of Oral Diseases & National Clinical Research Center for Oral Diseases & Department of Oral and Maxillofacial Surgery, West China Hospital of Stomatology, Sichuan University, No. 14 Section 3 Renminnan Road, Chengdu 610041, Sichuan Province, China. 475393040@qq.com
Key Words	Radiography; Artificial intelligence; Machine learning; Deep learning; Oral surgery; Maxillofacial surgery
Core Tip	A dramatic increase in medical imaging data has exceeded the ability of clinicians to process and analyze, which calls for higher-level analytic tools. Machine learning-based image analysis is useful for extracting key information to improve diagnostic accuracy and treatment efficacy. In this review, we summarize the applications of machine learning in oral and maxillofacial surgery as well as its current problems and solutions.
Publish Date	2021-12-28 12:39
Citation	Yan KX, Liu L, Li H. Application of machine learning in oral and maxillofacial surgery. Artif Intell Med Imaging 2021; 2(6): 104-114
URL	https://www.wjgnet.com/2644-3260/full/v2/i6/104.htm
DOI	https://dx.doi.org/10.35711/aimi.v2.i6.104

Full Article (PDF)	AIMI-2-104.pdf
Full Article (Word)	AIMI-2-104.docx
Manuscript File	73882_Auto_Edited-ML_WangTQ.docx
Answering Reviewers	73882-Answering reviewers.pdf
Audio Core Tip	73882-Audio core tip.mp3
Conflict-of-Interest Disclosure Form	73882-Conflict-of-interest statement.pdf
Copyright License Agreement	73882-Copyright license agreement.pdf
Approved Grant Application Form(s) or Funding Agency Copy of any Approval Document(s)	73882-Grant application form(s).pdf
Non-Native Speakers of English Editing Certificate	73882-Language certificate.pdf
Peer-review Report	73882-Peer-review(s).pdf
Scientific Misconduct Check	73882-Bing-Liu M-2.png
Scientific Editor Work List	73882-Scientific editor work list.pdf