Divergent and Convergent Imaging Markers Between Bipolar and Unipolar Depression Based on Machine Learning-Reference-Cited by-同舟云学术

Divergent and Convergent Imaging Markers Between Bipolar and Unipolar Depression Based on Machine Learning

Published:2022-08 Issue:8 Volume:26 Page:4100-4110
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Zhang Huifeng¹^ORCID,Zhou Zhen²^ORCID,Ding Lei¹,Wu Chuangxin¹,Qiu Meihui¹,Huang Yueqi¹,Jin Feng¹,Shen Ting¹,Yang Yao¹,Hsu Li-Ming³,Wang Jinhong¹,Zhang Han⁴^ORCID,Shen Dinggang⁴^ORCID,Peng Daihui¹^ORCID

Affiliation:

1. Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China

2. Center for Biomedical Image Computing and Analytics, Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA

3. Department of Radiology and BRIC, University of North Carolina, Chapel Hill, NC, USA

4. School of Biomedical Engineering, ShanghaiTech University, Shanghai, China

Funder

National Natural Science Foundation of China

Science and Technology Commission of Shanghai Municipality

Key Clinical Research Program of Shanghai Mental Health Center

Cross-Disciplinary and Translational Medical Research of Shanghai Jiao Tong University

Shanghai Pilot Program for Basic Research – Chinese Academy of Science

NIH

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/9855434/09756278.pdf?arnumber=9756278

Reference50 articles.

1. Tuning of olfactory cortex ventral tenia tecta neurons to distinct task elements of goal-directed behavior

2. The Association Between Olfaction and Depression: A Systematic Review

3. Functional hypergraph uncovers novel covariant structures over neurodevelopment

4. Saliency, switching, attention and control: a network model of insula function

5. The default mode network and self-referential processes in depression

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