Towards Disease-Aware Self-Supervised Dynamic Brain Network Learning For Mental Diagnosis-Reference-Cited by-同舟云学术

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Towards Disease-Aware Self-Supervised Dynamic Brain Network Learning For Mental Diagnosis

Published:2024-04-14 Issue: Volume: Page:2270-2274
ISSN:
Container-title:ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Jin Zhiyong¹,Wen Guangqi¹,Cao Peng¹,Liu Lingwen¹,Yang Jinzhu¹,Zhu Xinrong²,Zaiane Osmar R.³,Wang Fei²

Affiliation:

1. Northeastern University,Computer Science and Engineering,Shenyang,China

2. Nanjing Medical University,Early Intervention Unit,Department of Psychiatry Affiliated Nanjing Brain Hospital,Nanjing,China

3. University of Alberta,Alberta Machine Intelligence Institute,Edmonton, Alberta,Canada

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10445798/10445803/10446417.pdf?arnumber=10446417

Reference17 articles.

1. A computer-aided diagnosis system for brain tumors based on artificial intelligence algorithms

2. Tracking Whole-Brain Connectivity Dynamics in the Resting State

3. The Chronnectome: Time-Varying Connectivity Networks as the Next Frontier in fMRI Data Discovery

4. BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis

5. Functional annotation of human cognitive states using deep graph convolution

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