Deep learning identifies robust gender differences in functional brain organization and their dissociable links to clinical symptoms in autism
Background Autism spectrum disorder (ASD) is a highly heterogeneous disorder that affects
nearly 1 in 189 females and 1 in 42 males. However, the neurobiological basis of gender�…
nearly 1 in 189 females and 1 in 42 males. However, the neurobiological basis of gender�…
[HTML][HTML] Network-specific sex differentiation of intrinsic brain function in males with autism
Background The male predominance in the prevalence of autism spectrum disorder (ASD)
has motivated research on sex differentiation in ASD. Multiple sources of evidence have�…
has motivated research on sex differentiation in ASD. Multiple sources of evidence have�…
[HTML][HTML] Sex differences in cortical volume and gyrification in autism
Background Male predominance is a prominent feature of autism spectrum disorders (ASD),
with a reported male to female ratio of 4: 1. Because of the overwhelming focus on males�…
with a reported male to female ratio of 4: 1. Because of the overwhelming focus on males�…
Robust, generalizable, and interpretable artificial intelligence–derived brain fingerprints of autism and social communication symptom severity
Background Autism spectrum disorder (ASD) is among the most pervasive
neurodevelopmental disorders, yet the neurobiology of ASD is still poorly understood�…
neurodevelopmental disorders, yet the neurobiology of ASD is still poorly understood�…
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] Large-scale brain functional network integration for discrimination of autism using a 3-D deep learning model
M Yang, M Cao, Y Chen, Y Chen, G Fan…�- Frontiers in human�…, 2021 - frontiersin.org
Goal Brain functional networks (BFNs) constructed using resting-state functional magnetic
resonance imaging (fMRI) have proven to be an effective way to understand aberrant�…
resonance imaging (fMRI) have proven to be an effective way to understand aberrant�…
Machine learning methods for brain network classification: Application to autism diagnosis using cortical morphological networks
Background Autism spectrum disorder (ASD) affects the brain connectivity at different levels.
Nonetheless, non-invasively distinguishing such effects using magnetic resonance imaging�…
Nonetheless, non-invasively distinguishing such effects using magnetic resonance imaging�…
[HTML][HTML] Functional connectivity classification of autism identifies highly predictive brain features but falls short of biomarker standards
Objectives Autism spectrum disorders (ASD) are diagnosed based on early-manifesting
clinical symptoms, including markedly impaired social communication. We assessed the�…
clinical symptoms, including markedly impaired social communication. We assessed the�…
Contrastive machine learning reveals the structure of neuroanatomical variation within autism
Autism spectrum disorder (ASD) is highly heterogeneous. Identifying systematic individual
differences in neuroanatomy could inform diagnosis and personalized interventions. The�…
differences in neuroanatomy could inform diagnosis and personalized interventions. The�…
The link between autism and sex-related neuroanatomy, and associated cognition and gene expression
Objective: The male preponderance in prevalence of autism is among the most pronounced
sex ratios across neurodevelopmental conditions. The authors sought to elucidate the�…
sex ratios across neurodevelopmental conditions. The authors sought to elucidate the�…
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