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 …
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 …
Identifying autism from resting-state fMRI using long short-term memory networks
NC Dvornek, P Ventola, KA Pelphrey… - Machine Learning in …, 2017 - Springer
Functional magnetic resonance imaging (fMRI) has helped characterize the
pathophysiology of autism spectrum disorders (ASD) and carries promise for producing …
pathophysiology of autism spectrum disorders (ASD) and carries promise for producing …
Identifying autism spectrum disorder from resting-state fMRI using deep belief network
With the increasing prevalence of autism spectrum disorder (ASD), it is important to identify
ASD patients for effective treatment and intervention, especially in early childhood …
ASD patients for effective treatment and intervention, especially in early childhood …
Towards a brain‐based predictome of mental illness
Neuroimaging‐based approaches have been extensively applied to study mental illness in
recent years and have deepened our understanding of both cognitively healthy and …
recent years and have deepened our understanding of both cognitively healthy and …
A general prediction model for the detection of ADHD and Autism using structural and functional MRI
This work presents a novel method for learning a model that can diagnose Attention Deficit
Hyperactivity Disorder (ADHD), as well as Autism, using structural texture and functional …
Hyperactivity Disorder (ADHD), as well as Autism, using structural texture and functional …
DeepFMRI: End-to-end deep learning for functional connectivity and classification of ADHD using fMRI
Background Resting state fMRI has emerged as a popular neuroimaging method for
automated recognition and classification of brain disorders. Attention Deficit Hyperactivity …
automated recognition and classification of brain disorders. Attention Deficit Hyperactivity …
A systematic review of structural MRI biomarkers in autism spectrum disorder: A machine learning perspective
Abstract Autism Spectrum Disorder (ASD) affects approximately 1% of the population and
leads to impairments in social interaction, communication and restricted, repetitive …
leads to impairments in social interaction, communication and restricted, repetitive …
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 …