A Region-Based Feature Extraction Method for Rs-fMRI of Depressive Disorder Classification-Reference-Cited by-同舟云学术

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A Region-Based Feature Extraction Method for Rs-fMRI of Depressive Disorder Classification

Published:2020-07 Issue: Volume: Page:
ISSN:
Container-title:2020 International Conference on Computer Vision, Image and Deep Learning (CVIDL)
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Author:

Jin Jing,Huang Linlin

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9270288/9270409/09270514.pdf?arnumber=9270514

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multi-feature concatenation and multi-classifier stacking: An interpretable and generalizable machine learning method for MDD discrimination with rsfMRI;NeuroImage;2024-01

2. Cross-Domain Identification of Multisite Major Depressive Disorder Using End-to-End Brain Dynamic Attention Network;IEEE Transactions on Neural Systems and Rehabilitation Engineering;2024

3. EEG coherences of the fronto-limbic circuit between patients with major depressive disorder and healthy controls;Journal of Affective Disorders;2023-06

4. Finding Essential Parts of the Brain in rs-fMRI Can Improve ADHD Diagnosis Using Deep Learning;IEEE Access;2023

5. A systematic review on the potential use of machine learning to classify major depressive disorder from healthy controls using resting state fMRI measures;Neuroscience & Biobehavioral Reviews;2023-01

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