[HTML][HTML] Large-scale brain functional network integration for discrimination of autism using a 3-D deep learning model

M Yang, M Cao, Y Chen, Y Chen, G Fan… - Frontiers in human …, 2021 - frontiersin.org
Goal Brain functional networks (BFNs) constructed using resting-state functional magnetic
resonance imaging (fMRI) have proven to be an effective way to understand aberrant …

Functional connectivity patterns of autism spectrum disorder identified by deep feature learning

H Choi - arXiv preprint arXiv:1707.07932, 2017 - arxiv.org
Autism spectrum disorder (ASD) is regarded as a brain disease with globally disrupted
neuronal networks. Even though fMRI studies have revealed abnormal functional …

Artificial neural network inspired by neuroimaging connectivity: application in autism spectrum disorder

K Byeon, J Kwon, J Hong, H Park - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
Distinguishing the autism spectrum disorder (ASD) from typical control (TC) using resting-
state functional magnetic resonance imaging (rs-fMRI) is very difficult because ASD has …

A deep learning method for autism spectrum disorder identification based on interactions of hierarchical brain networks

N Qiang, J Gao, Q Dong, J Li, S Zhang, H Liang… - Behavioural Brain …, 2023 - Elsevier
Background It has been recently shown that deep learning models exhibited remarkable
performance of representing functional Magnetic Resonance Imaging (fMRI) data for the …

Improving diagnosis of autism spectrum disorder and disentangling its heterogeneous functional connectivity patterns using capsule networks

Z Jiao, H Li, Y Fan - 2020 IEEE 17th international symposium …, 2020 - ieeexplore.ieee.org
Functional connectivity (FC) analysis is an appealing tool to aid diagnosis and elucidate the
neurophysiological underpinnings of autism spectrum disorder (ASD). Many machine …

[HTML][HTML] Diagnosing autism spectrum disorder from brain resting-state functional connectivity patterns using a deep neural network with a novel feature selection …

X Guo, KC Dominick, AA Minai, H Li… - Frontiers in …, 2017 - frontiersin.org
The whole-brain functional connectivity (FC) pattern obtained from resting-state functional
magnetic resonance imaging data are commonly applied to study neuropsychiatric …

A convolutional neural network combined with prototype learning framework for brain functional network classification of autism spectrum disorder

Y Liang, B Liu, H Zhang - IEEE Transactions on Neural …, 2021 - ieeexplore.ieee.org
The application of deep learning methods in brain disease diagnosis is becoming a new
research hotspot. This study constructed brain functional networks based on the functional …

[HTML][HTML] Diagnosis of autism spectrum disorders using multi-level high-order functional networks derived from resting-state functional mri

F Zhao, H Zhang, I Rekik, Z An, D Shen - Frontiers in human …, 2018 - frontiersin.org
Functional brain networks derived from resting-state functional magnetic resonance imaging
(rs-fMRI) have been widely used for Autism Spectrum Disorder (ASD) diagnosis. Typically …

Classification of ASD based on fMRI data with deep learning

L Shao, C Fu, Y You, D Fu - Cognitive Neurodynamics, 2021 - Springer
Autism spectrum disorder (ASD) is a neuro-developmental disorder that affects the social
abilities of patients. Studies have shown that a small number of abnormal functional …

[HTML][HTML] Functional connectivity classification of autism identifies highly predictive brain features but falls short of biomarker standards

M Plitt, KA Barnes, A Martin - NeuroImage: Clinical, 2015 - Elsevier
Objectives Autism spectrum disorders (ASD) are diagnosed based on early-manifesting
clinical symptoms, including markedly impaired social communication. We assessed the …