Modeling the dynamic brain network representation for autism spectrum disorder diagnosis

[1] Nogay HS(2020)Machine learning (ML) for the diagnosis of autism spectrum disorder (ASD) using brain imaging Reviews in the Neurosciences 31 825-841

[2] Adeli H(2019)Diagnosis of autism spectrum disorder based on complex network features Computer Methods and Programs in Biomedicine 177 277-283

[3] Bajestani GS(2018)Identification of autism spectrum disorder using deep learning and the abide dataset NeuroImage: Clinical 17 16-23

[4] Behrooz M(2020)Prevalence of autism spectrum disorder among children aged 8 years-autism and developmental disabilities monitoring network, 11 sites, united states, 2016 MMWR Surveillance Summaries 69 1-534

[5] Khani AG(2021)Multi-model and multi-slice ensemble learning architecture based on 2D convolutional neural networks for Alzheimer’s disease diagnosis Computers in Biology and Medicine 136 104678-378

[6] Nouri-Baygi M(2010)Exploring the brain network: a review on resting-state fmri functional connectivity European Neuropsychopharmacology 20 519-2252

[7] Mollaei A(2020)Hi-GCN: a hierarchical graph convolution network for graph embedding learning of brain network and brain disorders prediction Computers in Biology and Medicine 127 104096-94

[8] Heinsfeld AS(2013)Dynamic functional connectivity: promise, issues, and interpretations Neuroimage 80 360-4227

[9] Franco AR(2019)Spatial-temporal dependency modeling and network hub detection for functional MRI analysis via convolutional-recurrent network IEEE Transactions on Biomedical Engineering 67 2241-655

[10] Craddock RC(2018)Integration of temporal and spatial properties of dynamic connectivity networks for automatic diagnosis of brain disease Medical Image Analysis 47 81-123

[1] Nogay HS(2020)Machine learning (ML) for the diagnosis of autism spectrum disorder (ASD) using brain imaging Reviews in the Neurosciences 31 825-841

[2] Adeli H(2019)Diagnosis of autism spectrum disorder based on complex network features Computer Methods and Programs in Biomedicine 177 277-283

[3] Bajestani GS(2018)Identification of autism spectrum disorder using deep learning and the abide dataset NeuroImage: Clinical 17 16-23

[4] Behrooz M(2020)Prevalence of autism spectrum disorder among children aged 8 years-autism and developmental disabilities monitoring network, 11 sites, united states, 2016 MMWR Surveillance Summaries 69 1-534

[5] Khani AG(2021)Multi-model and multi-slice ensemble learning architecture based on 2D convolutional neural networks for Alzheimer’s disease diagnosis Computers in Biology and Medicine 136 104678-378

[6] Nouri-Baygi M(2010)Exploring the brain network: a review on resting-state fmri functional connectivity European Neuropsychopharmacology 20 519-2252

[7] Mollaei A(2020)Hi-GCN: a hierarchical graph convolution network for graph embedding learning of brain network and brain disorders prediction Computers in Biology and Medicine 127 104096-94

[8] Heinsfeld AS(2013)Dynamic functional connectivity: promise, issues, and interpretations Neuroimage 80 360-4227

[9] Franco AR(2019)Spatial-temporal dependency modeling and network hub detection for functional MRI analysis via convolutional-recurrent network IEEE Transactions on Biomedical Engineering 67 2241-655

[10] Craddock RC(2018)Integration of temporal and spatial properties of dynamic connectivity networks for automatic diagnosis of brain disease Medical Image Analysis 47 81-123