Publication Name	World Journal of Psychiatry
Manuscript ID	97212
Country	China

Category	Clinical Neurology
Manuscript Type	Observational Study
Article Title	Resting-state functional magnetic resonance imaging and support vector machines for the diagnosis of major depressive disorder in adolescents
Manuscript Source	Invited Manuscript
All Author List	Zhi-Hui Yu, Ren-Qiang Yu, Xing-Yu Wang, Wen-Yu Ren, Xiao-Qin Zhang, Wei Wu, Xiao Li, Lin-Qi Dai and Ya-Lan Lv
Funding Agency and Grant Number
Corresponding Author	Ren-Qiang Yu, PhD, Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, No. 1 Youyi Road, Yuzhong District, Chongqing 400016, China. yurenqiang@hospital.cqmu.edu.cn
Key Words	Major depressive disorder; Adolescent; Support vector machine; Machine learning; Resting-state functional magnetic resonance imaging; Neuroimaging; Biomarker
Core Tip	We want to explore the potential neuroimaging biomarkers of adolescents with major depressive disorder using resting-state functional magnetic resonance imaging and support vector machines. The results showed that using the abnormal functional connectivity value of the right linguistic gyrus as a biomarker to distinguish patients and healthy controls had certain advantages, which was of great significance for the early diagnosis and treatment of adolescent major depressive disorder.
Citation	<p>Yu ZH, Yu RQ, Wang XY, Ren WY, Zhang XQ, Wu W, Li X, Dai LQ, Lv YL. Resting-state functional magnetic resonance imaging and support vector machines for the diagnosis of major depressive disorder in adolescents. <i>World J Psychiatry</i> 2024; 14(11): 1696-1707</p>

Received	2024-05-26 07:07
Peer-Review Started	2024-05-26 07:07
To Make the First Decision
Return for Revision	2024-09-30 09:53
Revised	2024-10-09 14:52
Second Decision	2024-10-30 02:37
Accepted by Journal Editor-in-Chief
Accepted by Executive Editor-in-Chief	2024-10-30 13:20
Articles in Press	2024-10-30 13:20
Publication Fee Transferred
Edit the Manuscript by Language Editor
Typeset the Manuscript	2024-11-01 03:28

ISSN	2220-3206 (online)
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