Deep learning for neuroimaging-based diagnosis and rehabilitation of autism spectrum disorder: a review

M Khodatars, A Shoeibi, D Sadeghi… - Computers in biology …, 2021 - Elsevier
Abstract Accurate diagnosis of Autism Spectrum Disorder (ASD) followed by effective
rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) …

Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review

P Moridian, N Ghassemi, M Jafari… - Frontiers in Molecular …, 2022 - frontiersin.org
Autism spectrum disorder (ASD) is a brain condition characterized by diverse signs and
symptoms that appear in early childhood. ASD is also associated with communication …

Braingnn: Interpretable brain graph neural network for fmri analysis

X Li, Y Zhou, N Dvornek, M Zhang, S Gao… - Medical Image …, 2021 - Elsevier
Understanding which brain regions are related to a specific neurological disorder or
cognitive stimuli has been an important area of neuroimaging research. We propose …

Deep learning for brain disorder diagnosis based on fMRI images

W Yin, L Li, FX Wu - Neurocomputing, 2022 - Elsevier
In modern neuroscience and clinical study, neuroscientists and clinicians often use non-
invasive imaging techniques to validate theories and computational models, observe brain …

A review of Hidden Markov models and Recurrent Neural Networks for event detection and localization in biomedical signals

Y Khalifa, D Mandic, E Sejdić - Information Fusion, 2021 - Elsevier
Biomedical signals carry signature rhythms of complex physiological processes that control
our daily bodily activity. The properties of these rhythms indicate the nature of interaction …

[HTML][HTML] Deep learning applications for the classification of psychiatric disorders using neuroimaging data: systematic review and meta-analysis

M Quaak, L van de Mortel, RM Thomas… - NeuroImage: Clinical, 2021 - Elsevier
Deep learning (DL) methods have been increasingly applied to neuroimaging data to
identify patients with psychiatric and neurological disorders. This review provides an …

[HTML][HTML] Representation learning of resting state fMRI with variational autoencoder

JH Kim, Y Zhang, K Han, Z Wen, M Choi, Z Liu - NeuroImage, 2021 - Elsevier
Resting state functional magnetic resonance imaging (rsfMRI) data exhibits complex but
structured patterns. However, the underlying origins are unclear and entangled in rsfMRI …

A robust DWT–CNN‐based CAD system for early diagnosis of autism using task‐based fMRI

R Haweel, A Shalaby, A Mahmoud, N Seada… - Medical …, 2021 - Wiley Online Library
Purpose Task‐based fMRI (TfMRI) is a diagnostic imaging modality for observing the effects
of a disease or other condition on the functional activity of the brain. Autism spectrum …

A machine learning approach for grading autism severity levels using task-based functional MRI

R Haweel, O Dekhil, A Shalaby… - … on Imaging Systems …, 2019 - ieeexplore.ieee.org
Autism is a developmental disorder associated with difficulties in communication and social
interaction. Autism diagnostic observation schedule (ADOS) is considered the gold standard …

A novel framework for grading autism severity using task-based fmri

R Haweel, O Dekhil, A Shalaby… - 2020 IEEE 17th …, 2020 - ieeexplore.ieee.org
Autism is a developmental disorder associated with difficulties in communication and social
interaction. Currently, the gold standard in autism diagnosis is the autism diagnostic …