AIMC Topic: Autism Spectrum Disorder

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Natural language processing (NLP) tools in extracting biomedical concepts from research articles: a case study on autism spectrum disorder.

BMC medical informatics and decision making
BACKGROUND: Natural language processing (NLP) tools can facilitate the extraction of biomedical concepts from unstructured free texts, such as research articles or clinical notes. The NLP software tools CLAMP, cTAKES, and MetaMap are among the most w...

Detection of eye contact with deep neural networks is as accurate as human experts.

Nature communications
Eye contact is among the most primary means of social communication used by humans. Quantification of eye contact is valuable as a part of the analysis of social roles and communication skills, and for clinical screening. Estimating a subject's looki...

Feature replacement methods enable reliable home video analysis for machine learning detection of autism.

Scientific reports
Autism Spectrum Disorder is a neuropsychiatric condition affecting 53 million children worldwide and for which early diagnosis is critical to the outcome of behavior therapies. Machine learning applied to features manually extracted from readily acce...

Deep-Learning-Based Detection of Infants with Autism Spectrum Disorder Using Auto-Encoder Feature Representation.

Sensors (Basel, Switzerland)
Autism spectrum disorder (ASD) is a developmental disorder with a life-span disability. While diagnostic instruments have been developed and qualified based on the accuracy of the discrimination of children with ASD from typical development (TD) chil...

Identifying individuals with autism spectrum disorder based on the principal components of whole-brain phase synchrony.

Neuroscience letters
Autism spectrum disorder (ASD) is a brain disorder that develops during an early stage of childhood. Previous neuroimaging-based diagnostic models for ASD were based on static functional connectivity (FC). The nonlinear complexity of brain connectivi...

Robot dramas may improve joint attention of Chinese-speaking low-functioning children with autism: stepped wedge trials.

Disability and rehabilitation. Assistive technology
INTRODUCTION: Children with autism spectrum disorder (ASD), especially those with low cognitive functioning, have deficits in joint attention. Previous research has found that these children are interested in engaging with social robots.

Prediction and prioritization of autism-associated long non-coding RNAs using gene expression and sequence features.

BMC bioinformatics
BACKGROUND: Autism spectrum disorders (ASD) refer to a range of neurodevelopmental conditions, which are genetically complex and heterogeneous with most of the genetic risk factors also found in the unaffected general population. Although all the cur...

Topology-guided cyclic brain connectivity generation using geometric deep learning.

Journal of neuroscience methods
BACKGROUND: There is a growing need for analyzing medical data such as brain connectomes. However, the unavailability of large-scale training samples increases risks of model over-fitting. Recently, deep learning (DL) architectures quickly gained mom...

Single Volume Image Generator and Deep Learning-Based ASD Classification.

IEEE journal of biomedical and health informatics
Autism spectrum disorder (ASD) is an intricate neuropsychiatric brain disorder characterized by social deficits and repetitive behaviors. Deep learning approaches have been applied in clinical or behavioral identification of ASD; most erstwhile model...

Automated identification of postural control for children with autism spectrum disorder using a machine learning approach.

Journal of biomechanics
It is unclear whether postural sway characteristics could be used as diagnostic biomarkers for autism spectrum disorder (ASD). The purpose of this study was to develop and validate an automated identification of postural control patterns in children ...