Identification of Autism Spectrum Disorder With Functional Graph Discriminative Network
Autism spectrum disorder (ASD) is a specific brain disease that causes communication impairments and restricted interests. Functional connectivity analysis methodology is widely used in neuroscience research and shows much potential in discriminating ASD patients from healthy controls. However, due...
Main Authors: | Jingcong Li, Fei Wang, Jiahui Pan, Zhenfu Wen |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2021-10-01
|
Series: | Frontiers in Neuroscience |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fnins.2021.729937/full |
Similar Items
-
Evaluation of Altered Functional Connections in Male Children With Autism Spectrum Disorders on Multiple-Site Data Optimized With Machine Learning
by: Giovanna Spera, et al.
Published: (2019-09-01) -
A Deep Learning Approach to Predict Autism Spectrum Disorder Using Multisite Resting-State fMRI
by: Faria Zarin Subah, et al.
Published: (2021-04-01) -
Multi-Scale Graph Representation Learning for Autism Identification With Functional MRI
by: Ying Chu, et al.
Published: (2022-01-01) -
Diagnosis of Autism Spectrum Disorder (ASD) Using Recursive Feature Elimination–Graph Neural Network (RFE–GNN) and Phenotypic Feature Extractor (PFE)
by: Jiahong Yang, et al.
Published: (2023-12-01) -
Automated Detection of Autism Spectrum Disorder Using a Convolutional Neural Network
by: Zeinab Sherkatghanad, et al.
Published: (2020-01-01)