Publication Name	World Journal of Psychiatry
Manuscript ID	90160
Country	China

Received	2023-11-25 15:02
Peer-Review Started	2023-11-25 15:03
To Make the First Decision
Return for Revision	2023-12-06 03:18
Revised	2023-12-18 09:00
Second Decision	2024-01-24 02:46
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2024-01-24 06:59
Articles in Press	2024-01-24 06:59
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2024-02-01 00:20
Publish the Manuscript Online	2024-02-06 06:16

ISSN	2220-3206 (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: https://creativecommons.org/Licenses/by-nc/4.0/
Copyright	© The Author(s) 2024. 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	Computer Science, Artificial Intelligence
Manuscript Type	Minireviews
Article Title	Automatic recognition of depression based on audio and video: A review
Manuscript Source	Invited Manuscript
All Author List	Meng-Meng Han, Xing-Yun Li, Xin-Yu Yi, Yun-Shao Zheng, Wei-Li Xia, Ya-Fei Liu and Qing-Xiang Wang
Funding Agency and Grant Number	Funding Agency Grant Number Shandong Provincial Natural Science Foundation ZR2021MF079 Shandong Province Key R and D Program 2021SFGC0504 Science and Technology Development Plan of Jinan (Clinical Medicine Science and Technology Innovation Plan) 202225054
Corresponding Author	Qing-Xiang Wang, PhD, Associate Professor, Shandong Mental Health Center, Shandong University, No. 49 Wenhua East Road, Jinan 250014, Shandong Province, China. wangqx@qlu.edu.cn
Key Words	Depression recognition; Deep learning; Automatic depression estimation System; Audio processing; Image processing; Feature fusion; Future development
Core Tip	The automatic recognition of depression based on deep learning has gradually become a research hotspot. Researchers have proposed automatic depression estimation (ADE) systems utilizing sound and video data to assist physicians in screening for depression. This article provides an overview of the latest research on ADE systems, focusing on sound and video datasets, current research challenges, and future directions.
Publish Date	2024-02-06 06:16
Citation	Han MM, Li XY, Yi XY, Zheng YS, Xia WL, Liu YF, Wang QX. Automatic recognition of depression based on audio and video: A review. World J Psychiatry 2024; 14(2): 225-233
URL	https://www.wjgnet.com/2220-3206/full/v14/i2/225.htm
DOI	https://dx.doi.org/10.5498/wjp.v14.i2.225

Full Article (PDF)	WJP-14-225-with-cover.pdf
Full Article (Word)	WJP-14-225.docx
Manuscript File	90160_Auto_Edited-YJP.docx
Answering Reviewers	90160-Answering reviewers.pdf
Audio Core Tip	90160-Audio core tip.mp3
Conflict-of-Interest Disclosure Form	90160-Conflict-of-interest statement .pdf
Copyright License Agreement	90160-Copyright license agreement.pdf
Approved Grant Application Form(s) or Funding Agency Copy of any Approval Document(s)	90160-Grant application form(s).pdf
Non-Native Speakers of English Editing Certificate	90160-Language certificate.pdf
Peer-review Report	90160-Peer-review(s).pdf
Scientific Misconduct Check	90160-Bing-Qu XL-2.png
Scientific Editor Work List	90160-Scientific editor work list.pdf
CrossCheck Report	90160-CrossCheck report.pdf