STANet: A Novel Spatio-Temporal Aggregation Network for Depression Classification with Small and Unbalanced FMRI Data

<b>Background</b>: Early diagnosis of depression is crucial for effective treatment and suicide prevention. Traditional methods rely on self-report questionnaires and clinical assessments, lacking objective biomarkers. Combining functional magnetic resonance imaging (fMRI) with artificia...

Full description

Saved in:

Bibliographic Details
Main Authors:	Wei Zhang, Weiming Zeng, Hongyu Chen, Jie Liu, Hongjie Yan, Kaile Zhang, Ran Tao, Wai Ting Siok, Nizhuan Wang
Format:	Article
Language:	English
Published:	MDPI AG 2024-11-01
Series:	Tomography
Subjects:	depression fMRI independent component analysis (ICA) GRU synthetic minority over-sampling technique (SMOTE) adaptive fusion weight
Online Access:	https://www.mdpi.com/2379-139X/10/12/138
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!

STANet: A Novel Spatio-Temporal Aggregation Network for Depression Classification with Small and Unbalanced FMRI Data

Similar Items