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Cited by in CrossRef
For: 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. World J Psychiatry 2024; 14(11): 1696-1707 [PMID: 39564181 DOI: 10.5498/wjp.v14.i11.1696]
URL: https://www.wjgnet.com/2220-3206/full/v14/i11/1696.htm
Number Citing Articles
1
Haewon Byeon. Unveiling the invisible: How cutting-edge neuroimaging transforms adolescent depression diagnosisWorld Journal of Psychiatry 2025; 15(5): 102953 doi: 10.5498/wjp.v15.i5.102953
2
Zhong Li, Yanrui Shen, Meng Zhang, Xuekun Li, Baolin Wu. Multivariate Classification of Adolescent Major Depressive Disorder Using Whole-brain Functional ConnectivityAcademic Radiology 2025;  doi: 10.1016/j.acra.2025.02.052
3
Shi-Qi Yin, Ying-Huan Li. Advancing the diagnosis of major depressive disorder: Integrating neuroimaging and machine learningWorld Journal of Psychiatry 2025; 15(3): 103321 doi: 10.5498/wjp.v15.i3.103321
4
Qianqian Li, Li Qi, Gu Zhang, Jiajia Hao, Qiufang Ren, Jian Guan, Yuqian Zhan, Yue Yu, Jinying Yang, Kai Wang, Tongjian Bai. Disrupted interhemispheric functional and structural connectivity in patients with major depressive disorderProgress in Neuro-Psychopharmacology and Biological Psychiatry 2025; 139: 111374 doi: 10.1016/j.pnpbp.2025.111374