Adaptive Multimodal Neuroimage Integration for Major Depression Disorder Detection
Major depressive disorder (MDD) is one of the most common mental health disorders that can affect sleep, mood, appetite, and behavior of people. Multimodal neuroimaging data, such as functional and structural magnetic resonance imaging (MRI) scans, have been widely used in computer-aided detection o...
Main Authors: | Qianqian Wang, Long Li, Lishan Qiao, Mingxia Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2022-04-01
|
Series: | Frontiers in Neuroinformatics |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fninf.2022.856175/full |
Similar Items
-
Prediction of anxious depression using multimodal neuroimaging and machine learning
by: Enqi Zhou, et al.
Published: (2024-01-01) -
Biotypes of major depressive disorder: Neuroimaging evidence from resting-state default mode network patterns
by: Sugai Liang, et al.
Published: (2020-01-01) -
Neural activity in adults with major depressive disorder differs from that in healthy individuals: A resting-state functional magnetic resonance imaging study
by: Xiaofang Hou, et al.
Published: (2022-11-01) -
Alterations of functional connectivity of the lateral habenula in subclinical depression and major depressive disorder
by: Lei Yang, et al.
Published: (2022-09-01) -
Aberrant degree centrality of functional brain networks in subclinical depression and major depressive disorder
by: Lei Yang, et al.
Published: (2023-02-01)