Autism

Outcomes of a Robot-Assisted Social-Emotional Understanding Intervention for Young Children with Autism Spectrum Disorders.

This study is a randomized control trial aimed at testing the role of a human-assisted social robot as an intervention mediator in a socio-emotional understanding protocol for children with autism spectrum disorders (ASD). Fourteen children (4-8 years old) were randomly assigned to 10 sessions of a cognitive behavioural therapy (CBT) intervention implemented in a group setting either with or witho...

Multi-dimensional machine learning approaches for fruit shape phenotyping in strawberry.

BACKGROUND: Shape is a critical element of the visual appeal of strawberry fruit and is influenced by both genetic and non-genetic determinants. Current fruit phenotyping approaches for external characteristics in strawberry often rely on the human eye to make categorical assessments. However, fruit shape is an inherently multi-dimensional, continuously variable trait and not adequately described ...

Examining joint attention with the use of humanoid robots-A new approach to study fundamental mechanisms of social cognition.

This article reviews methods to investigate joint attention and highlights the benefits of new methodological approaches that make use of the most rec...

Modeling engagement in long-term, in-home socially assistive robot interventions for children with autism spectrum disorders.

Socially assistive robotics (SAR) has great potential to provide accessible, affordable, and personalized therapeutic interventions for children with ...

A Robot-Based Play-Drama Intervention May Improve the Joint Attention and Functional Play Behaviors of Chinese-Speaking Preschoolers with Autism Spectrum Disorder: A Pilot Study.

Children with autism spectrum disorder (ASD) have deficits in joint attention and play behaviors. We examined whether a robot-based play-drama interve...

Future Vision 2020 and Beyond-5 Critical Trends in Eye Research.

Ophthalmology has been at the forefront of many innovations in basic science and clinical research. The randomized prospective multicenter clinical tr...

Convolutional Neural Network Visualization for Identification of Risk Genes in Bipolar Disorder.

BACKGROUND: Bipolar disorder (BD) is a type of chronic emotional disorder with a complex genetic structure. However, its genetic molecular mechanism i...

Statistical and Machine Learning Methods for eQTL Analysis.

An immense amount of observable diversity exists for all traits and across global populations. In the post-genomic era, equipped with efficient sequen...

Preliminary Test of the Potential of Contact With Dogs to Elicit Spontaneous Imitation in Children and Adults With Severe Autism Spectrum Disorder.

IMPORTANCE: Finding strategies to enhance imitation skills in people with autism spectrum disorder (ASD) is of major clinical relevance.

[Autism spectrum disorder biomarkers based on biosignals, virtual reality and artificial intelligence].

It has been observed that the stratification of Autism Spectrum Disorders (ASD) generated by the current scales is not effective for the personalizati...

CHDGKB: a knowledgebase for systematic understanding of genetic variations associated with non-syndromic congenital heart disease.

Congenital heart disease (CHD) is one of the most common birth defects, with complex genetic and environmental etiologies. The reports of genetic vari...

Machine learning-based automated phenotyping of inflammatory nocifensive behavior in mice.

The discovery and development of new and potentially nonaddictive pain therapeutics requires rapid, yet clinically relevant assays of nociception in p...

Machine learning approach to identify a resting-state functional connectivity pattern serving as an endophenotype of autism spectrum disorder.

Endophenotype refers to a measurable and heritable component between genetics and diagnosis, and the same endophenotype is present in both individuals...

Diagnosis of Autism Spectrum Disorders in Young Children Based on Resting-State Functional Magnetic Resonance Imaging Data Using Convolutional Neural Networks.

Statistics show that the risk of autism spectrum disorder (ASD) is increasing in the world. Early diagnosis is most important factor in treatment of A...

Gene-gene interaction: the curse of dimensionality.

Identified genetic variants from genome wide association studies frequently show only modest effects on the disease risk, leading to the "missing heri...

CARERAID: Controlled Autonomous Robot for Early Detection and Rehabilitation of Autism and Intellectual Disability.

The Use of Artificial Intelligence in Screening and Diagnosis of Autism Spectrum Disorder: A Literature Review.

OBJECTIVES: The detection of autism spectrum disorder (ASD) is based on behavioral observations. To build a more objective datadriven method for scree...

Using Machine Learning and Natural Language Processing to Review and Classify the Medical Literature on Cancer Susceptibility Genes.

PURPOSE: The medical literature relevant to germline genetics is growing exponentially. Clinicians need tools that help to monitor and prioritize the ...

Teaching Digital, Block-Based Coding of Robots to High School Students with Autism Spectrum Disorder and Challenging Behavior.

The use of robots to teach students with autism spectrum disorder communication skills has basis in the literature; however, research investigating th...

Artificial intelligence in drug combination therapy.

Currently, the development of medicines for complex diseases requires the development of combination drug therapies. It is necessary because in many c...