AIMC Topic: Autism Spectrum Disorder

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Autism spectrum disorders detection based on multi-task transformer neural network.

BMC neuroscience
Autism Spectrum Disorders (ASD) are neurodevelopmental disorders that cause people difficulties in social interaction and communication. Identifying ASD patients based on resting-state functional magnetic resonance imaging (rs-fMRI) data is a promisi...

ASD-SWNet: a novel shared-weight feature extraction and classification network for autism spectrum disorder diagnosis.

Scientific reports
The traditional diagnostic process for autism spectrum disorder (ASD) is subjective, where early and accurate diagnosis significantly affects treatment outcomes and life quality. Thus, improving ASD diagnostic methods is critical. This paper proposes...

A Review on Autism Spectrum Disorder Screening by Artificial Intelligence Methods.

Journal of autism and developmental disorders
PURPOSE: With the increasing prevalence of autism spectrum disorders (ASD), the importance of early screening and diagnosis has been subject to considerable discussion. Given the subtle differences between ASD children and typically developing childr...

Exploring the potential of representation and transfer learning for anatomical neuroimaging: Application to psychiatry.

NeuroImage
The perspective of personalized medicine for brain disorders requires efficient learning models for anatomical neuroimaging-based prediction of clinical conditions. There is now a consensus on the benefit of deep learning (DL) in addressing many medi...

Attention-Like Multimodality Fusion With Data Augmentation for Diagnosis of Mental Disorders Using MRI.

IEEE transactions on neural networks and learning systems
The globally rising prevalence of mental disorders leads to shortfalls in timely diagnosis and therapy to reduce patients' suffering. Facing such an urgent public health problem, professional efforts based on symptom criteria are seriously overstretc...

Adversarial Learning Based Node-Edge Graph Attention Networks for Autism Spectrum Disorder Identification.

IEEE transactions on neural networks and learning systems
Graph neural networks (GNNs) have received increasing interest in the medical imaging field given their powerful graph embedding ability to characterize the non-Euclidean structure of brain networks based on magnetic resonance imaging (MRI) data. How...

Predicting autism traits from baby wellness records: A machine learning approach.

Autism : the international journal of research and practice
Timely identification of autism spectrum conditions is a necessity to enable children to receive the most benefit from early interventions. Emerging technological advancements provide avenues for detecting subtle, early indicators of autism from rout...

A hybrid CNN-SVM model for enhanced autism diagnosis.

PloS one
Autism is a representative disorder of pervasive developmental disorder. It exerts influence upon an individual's behavior and performance, potentially co-occurring with other mental illnesses. Consequently, an effective diagnostic approach proves to...

Multi-kernel Learning Fusion Algorithm Based on RNN and GRU for ASD Diagnosis and Pathogenic Brain Region Extraction.

Interdisciplinary sciences, computational life sciences
Autism spectrum disorder (ASD) is a complex, severe disorder related to brain development. It impairs patient language communication and social behaviors. In recent years, ASD researches have focused on a single-modal neuroimaging data, neglecting th...

Autism spectrum disorder diagnosis with EEG signals using time series maps of brain functional connectivity and a combined CNN-LSTM model.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: People with autism spectrum disorder (ASD) often have cognitive impairments. Effective connectivity between different areas of the brain is essential for normal cognition. Electroencephalography (EEG) has been widely used in...