Classification methods based on machine learning (ML) techniques are becoming
widespread analysis tools in neuroimaging studies. They have the potential to enhance the …

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by deficits
in social interaction and communication, as well as repetitive and restrictive behaviours. The …

Most psychiatric disorders are associated with subtle alterations in brain function and are
subject to large interindividual differences. Typically, the diagnosis of these disorders …

Abstract Autism Spectrum Disorder (ASD) is a brain disorder that is typically characterized
by deficits in social communication and interaction, as well as restrictive and repetitive …

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 …

Objectives Individual anatomical biomarkers have limited power for the classification of
autism. The present study introduces a multivariate classification approach using structural …

Autism spectrum disorder (ASD) is the fourth most common neurodevelopmental disorder,
with a prevalence of 1 in 160 children. Accurate diagnosis relies on experts, but such …

The identification of reliable brain endophenotypes of autism spectrum disorders (ASD) has
been hampered to date by the heterogeneity in the neuroanatomical abnormalities detected …

We designed a modular machine learning program that uses functional magnetic resonance
imaging (fMRI) data in order to distinguish individuals with autism spectrum disorders from …

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders with multiple
biological etiologies and highly variable symptoms. Using a novel analytical framework that …