Application of graph theory for identifying connectivity patterns in human brain networks: a systematic review
Background: Analysis of the human connectome using functional magnetic resonance
imaging (fMRI) started in the mid-1990s and attracted increasing attention in attempts to …
imaging (fMRI) started in the mid-1990s and attracted increasing attention in attempts to …
Deep learning for neuroimaging-based diagnosis and rehabilitation of autism spectrum disorder: a review
Abstract Accurate diagnosis of Autism Spectrum Disorder (ASD) followed by effective
rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) …
rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) …
Machine learning (ML) for the diagnosis of autism spectrum disorder (ASD) using brain imaging
Autism spectrum disorder (ASD) is a neurodevelopmental incurable disorder with a long
diagnostic period encountered in the early years of life. If diagnosed early, the negative …
diagnostic period encountered in the early years of life. If diagnosed early, the negative …
Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review
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 …
symptoms that appear in early childhood. ASD is also associated with communication …
rs-fMRI and machine learning for ASD diagnosis: a systematic review and meta-analysis
Abstract Autism Spectrum Disorder (ASD) diagnosis is still based on behavioral criteria
through a lengthy and time-consuming process. Much effort is being made to identify brain …
through a lengthy and time-consuming process. Much effort is being made to identify brain …
Diagnostic of autism spectrum disorder based on structural brain MRI images using, grid search optimization, and convolutional neural networks
In this study, an automatic autism diagnostic model based on sMRI is proposed. This
proposed model consists of two basic stages. The first stage is the preprocessing stage …
proposed model consists of two basic stages. The first stage is the preprocessing stage …
Artificial intelligence for brain diseases: A systematic review
Artificial intelligence (AI) is a major branch of computer science that is fruitfully used for
analyzing complex medical data and extracting meaningful relationships in datasets, for …
analyzing complex medical data and extracting meaningful relationships in datasets, for …
ASD-SAENet: a sparse autoencoder, and deep-neural network model for detecting autism spectrum disorder (ASD) using fMRI data
F Almuqhim, F Saeed - Frontiers in Computational Neuroscience, 2021 - frontiersin.org
Autism spectrum disorder (ASD) is a heterogenous neurodevelopmental disorder which is
characterized by impaired communication, and limited social interactions. The shortcomings …
characterized by impaired communication, and limited social interactions. The shortcomings …
From pattern classification to stratification: towards conceptualizing the heterogeneity of Autism Spectrum Disorder
Pattern classification and stratification approaches have increasingly been used in research
on Autism Spectrum Disorder (ASD) over the last ten years with the goal of translation …
on Autism Spectrum Disorder (ASD) over the last ten years with the goal of translation …
Autism spectrum disorder studies using fMRI data and machine learning: a review
M Liu, B Li, D Hu - Frontiers in Neuroscience, 2021 - frontiersin.org
Machine learning methods have been frequently applied in the field of cognitive
neuroscience in the last decade. A great deal of attention has been attracted to introduce …
neuroscience in the last decade. A great deal of attention has been attracted to introduce …