Multi-Stage Graph Fusion Networks for Major Depressive Disorder Diagnosis-Reference-Cited by-同舟云学术

Multi-Stage Graph Fusion Networks for Major Depressive Disorder Diagnosis

Published:2022-10-01 Issue:4 Volume:13 Page:1917-1928
ISSN:1949-3045
Container-title:IEEE Transactions on Affective Computing
language:
Short-container-title:IEEE Trans. Affective Comput.

Author:

Kong Youyong¹^ORCID,Niu Shuyi¹,Gao Heren¹,Yue Yingying²,Shu Huazhong¹^ORCID,Xie Chunming³,Zhang Zhijun³,Yuan Yonggui²^ORCID

Affiliation:

1. Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing, School of Computer Science and Engineering, Southeast University, Nanjing, Jiangsu, China

2. Department of Psychosomatic and Psychiatry, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China

3. Department of Neurology, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China

Funder

Natural Science Foundation of Jiangsu Province

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Human-Computer Interaction,Software

Link

http://xplorestaging.ieee.org/ielx7/5165369/9964459/09887870.pdf?arnumber=9887870

Reference74 articles.

1. Anomalous intrinsic connectivity within and between visual and auditory networks in major depressive disorder

2. Intrinsic connectomes are a predictive biomarker of remission in major depressive disorder

3. Altered Transcranial Magnetic Stimulation–Electroencephalographic Markers of Inhibition and Excitation in the Dorsolateral Prefrontal Cortex in Major Depressive Disorder

4. Single-nucleus transcriptomics of the prefrontal cortex in major depressive disorder implicates oligodendrocyte precursor cells and excitatory neurons

5. Hypofunction of left dorsolateral prefrontal cortex in depression during verbal fluency task: A multi-channel near-infrared spectroscopy study

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