The field of psychiatry is hampered by a lack of robust, reliable and valid biomarkers that can
aid in objectively diagnosing patients and providing individualized treatment …

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 …

In this paper we propose a novel method that provides contrastive explanations justifying the
classification of an input by a black box classifier such as a deep neural network. Given an …

Autism spectrum disorder (ASD) is characterized by deficits in social communication and
interaction. Since its discovery as a major functional brain system, the default mode network …

Resting-state functional magnetic resonance imaging (fMRI) is widely used in cognitive and
clinical neuroscience, but long-duration scans are currently needed to reliably characterize …

Abstract Machine learning techniques have gained prominence for the analysis of resting-
state functional Magnetic Resonance Imaging (rs-fMRI) data. Here, we present an overview …

Autism spectrum disorder is a construct used to describe individuals with a specific
combination of impairments in social communication and repetitive behaviours, highly …

Comparison of graph structure is a ubiquitous task in data analysis and machine learning,
with diverse applications in fields such as neuroscience, cyber security, social network …

Autism spectrum disorder is defined by two core symptoms: a deficit in social communication
and the presence of repetitive behaviors and/or restricted interests. Currently, there is no US …

Background Resting-state functional magnetic resonance imaging–based studies on
functional connectivity in autism spectrum disorder (ASD) have generated inconsistent …