[HTML][HTML] The functional brain organization of an individual allows prediction of measures of social abilities transdiagnostically in autism and attention-deficit …
Background Autism spectrum disorder and attention-deficit/hyperactivity disorder (ADHD)
are associated with complex changes as revealed by functional magnetic resonance …
are associated with complex changes as revealed by functional magnetic resonance …
Brain state differentiation and behavioral inflexibility in autism
Autism spectrum disorders (ASDs) are characterized by social impairments alongside
cognitive and behavioral inflexibility. While social deficits in ASDs have extensively been …
cognitive and behavioral inflexibility. While social deficits in ASDs have extensively been …
Distributed intrinsic functional connectivity patterns predict diagnostic status in large autism cohort
Diagnosis of autism spectrum disorder (ASD) currently relies on behavioral observations
because brain markers are unknown. Machine learning approaches can identify patterns in …
because brain markers are unknown. Machine learning approaches can identify patterns in …
[HTML][HTML] Crowdsourced validation of a machine-learning classification system for autism and ADHD
Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) together
affect> 10% of the children in the United States, but considerable behavioral overlaps …
affect> 10% of the children in the United States, but considerable behavioral overlaps …
Exploring the structural and strategic bases of autism spectrum disorders with deep learning
Deep learning models are applied in clinical research in order to diagnose disease.
However, diagnosing autism spectrum disorders (ASD) remains challenging due to its …
However, diagnosing autism spectrum disorders (ASD) remains challenging due to its …
[HTML][HTML] Single-participant structural similarity matrices lead to greater accuracy in classification of participants than function in autism in MRI
Background Autism has previously been characterized by both structural and functional
differences in brain connectivity. However, while the literature on single-subject derivations …
differences in brain connectivity. However, while the literature on single-subject derivations …
[HTML][HTML] Reproducible neuroimaging features for diagnosis of autism spectrum disorder with machine learning
CJ Mellema, KP Nguyen, A Treacher, A Montillo - Scientific reports, 2022 - nature.com
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 …
with a prevalence of 1 in 160 children. Accurate diagnosis relies on experts, but such …
[HTML][HTML] Enhancing diagnosis of autism with optimized machine learning models and personal characteristic data
Autism spectrum disorder (ASD) is a developmental disorder, affecting about 1% of the
global population. Currently, the only clinical method for diagnosing ASD are standardized …
global population. Currently, the only clinical method for diagnosing ASD are standardized …
[HTML][HTML] Exploring links between genotypes, phenotypes, and clinical predictors of response to early intensive behavioral intervention in autism spectrum disorder
V Eapen, R Črnčec, A Walter - Frontiers in human neuroscience, 2013 - frontiersin.org
Autism spectrum disorder (ASD) is amongst the most familial of psychiatric disorders. Twin
and family studies have demonstrated a monozygotic concordance rate of 70–90 …
and family studies have demonstrated a monozygotic concordance rate of 70–90 …
Salience network–based classification and prediction of symptom severity in children with autism
Importance Autism spectrum disorder (ASD) affects 1 in 88 children and is characterized by
a complex phenotype, including social, communicative, and sensorimotor deficits. Autism …
a complex phenotype, including social, communicative, and sensorimotor deficits. Autism …