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Autistic Disorder

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Evaluation of interpretability for deep learning algorithms in EEG emotion recognition: A case study in autism.

Artificial intelligence in medicine
Current models on Explainable Artificial Intelligence (XAI) have shown a lack of reliability when evaluating feature-relevance for deep neural biomarker classifiers. The inclusion of reliable saliency-maps for obtaining trustworthy and interpretable ...

Development and Validation of a Joint Attention-Based Deep Learning System for Detection and Symptom Severity Assessment of Autism Spectrum Disorder.

JAMA network open
IMPORTANCE: Joint attention, composed of complex behaviors, is an early-emerging social function that is deficient in children with autism spectrum disorder (ASD). Currently, no methods are available for objectively quantifying joint attention.

Motor differences in autism during a human-robot imitative gesturing task.

Clinical biomechanics (Bristol, Avon)
BACKGROUND: Difficulty with imitative gesturing is frequently observed as a clinical feature of autism. Current practices for assessment of imitative gesturing ability-behavioral observation and parent report-do not allow precise measurement of speci...

DeepGenePrior: A deep learning model for prioritizing genes affected by copy number variants.

PLoS computational biology
The genetic etiology of brain disorders is highly heterogeneous, characterized by abnormalities in the development of the central nervous system that lead to diminished physical or intellectual capabilities. The process of determining which gene driv...

Enhancing early autism diagnosis through machine learning: Exploring raw motion data for classification.

PloS one
In recent years, research has been demonstrating that movement analysis, utilizing machine learning methods, can be a promising aid for clinicians in supporting autism diagnostic process. Within this field of research, we aim to explore new models an...

Comprehensive exploration of multi-modal and multi-branch imaging markers for autism diagnosis and interpretation: insights from an advanced deep learning model.

Cerebral cortex (New York, N.Y. : 1991)
Autism spectrum disorder is a complex neurodevelopmental condition with diverse genetic and brain involvement. Despite magnetic resonance imaging advances, autism spectrum disorder diagnosis and understanding its neurogenetic factors remain challengi...

Seeing through a robot's eyes: A cross-sectional exploratory study in developing a robotic screening technology for autism.

Autism research : official journal of the International Society for Autism Research
The present exploratory cross-sectional case-control study sought to develop a reliable and scalable screening tool for autism using a social robot. The robot HUMANE, installed with computer vision and linked with recognition technology, detected the...

Assisted Robots in Therapies for Children with Autism in Early Childhood.

Sensors (Basel, Switzerland)
Children with autism spectrum disorder (ASD) have deficits that affect their social relationships, communication, and flexibility in reasoning. There are different types of treatment (pharmacological, educational, psychological, and rehabilitative). ...

Graph Node Classification to Predict Autism Risk in Genes.

Genes
This study explores the genetic risk associations with autism spectrum disorder (ASD) using graph neural networks (GNNs), leveraging the Sfari dataset and protein interaction network (PIN) data. We built a gene network with genes as nodes, chromosome...