Neurology

Autism

Latest AI and machine learning research in autism for healthcare professionals.

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A refined cell-of-origin classifier with targeted NGS and artificial intelligence shows robust predictive value in DLBCL.

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous entity of B-cell lymphoma. Cell-of-origin (...

Predicting the pathogenicity of protein coding mutations using Natural Language Processing.

DNA-Sequencing of tumor cells has revealed thousands of genetic mutations. However, cancer is caused...

Antidepressant pathways of the Chinese herb through genetic ontology analysis.

Active compounds and corresponding targets of the traditional Chinese herb, were obtained from syst...

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 ...

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 b...

The retina revolution: signaling pathway therapies, genetic therapies, mitochondrial therapies, artificial intelligence.

PURPOSE OF REVIEW: The aim of this article is to review and discuss the history, current state, and ...

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 metho...

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 persona...

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

The discovery and development of new and potentially nonaddictive pain therapeutics requires rapid, ...

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 env...

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. ...

Antibody Clustering Using a Machine Learning Pipeline that Fuses Genetic, Structural, and Physicochemical Properties.

Antibody V domain clustering is of paramount importance to a repertoire of immunology-related areas....

[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 cur...

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 (...

Statistical and Machine Learning Methods for eQTL Analysis.

An immense amount of observable diversity exists for all traits and across global populations. In th...

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 str...

Machine Learning by Ultrasonography for Genetic Risk Stratification of Thyroid Nodules.

IMPORTANCE: Thyroid nodules are common incidental findings. Ultrasonography and molecular testing ca...

Gene-gene interaction: the curse of dimensionality.

Identified genetic variants from genome wide association studies frequently show only modest effects...

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