Psychiatry

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

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Rich spectrum of neural field dynamics in the presence of short-term synaptic depression.

In continuous attractor neural networks (CANNs), spatially continuous information such as orientatio...

Sep 2015 26465541
Automated measurement of mouse social behaviors using depth sensing, video tracking, and machine learning.

A lack of automated, quantitative, and accurate assessment of social behaviors in mammalian animal m...

Sep 2015 26354123
Robot-Mediated Imitation Skill Training for Children With Autism.

Autism spectrum disorder (ASD) impacts 1 in 68 children in the U.S., with tremendous individual and ...

Sep 2015 26353376
The "Reading the Mind in the Eyes" Test: Complete Absence of Typical Sex Difference in ~400 Men and Women with Autism.

The "Reading the Mind in the Eyes" test (Eyes test) is an advanced test of theory of mind. Typical s...

Aug 2015 26313946
Analysis of NTSB Aircraft-Assisted Pilot Suicides: 1982-2014.

On March 24, 2015, a Germanwings aircraft crashed in the Alps. The suicidal copilot killed himself a...

Aug 2015 27094027
Assessing hippocampal development and language in early childhood: Evidence from a new application of the Automatic Segmentation Adapter Tool.

Volumetric assessments of the hippocampus and other brain structures during childhood provide useful...

Aug 2015 26279309
A Controlled Trial Using Natural Language Processing to Examine the Language of Suicidal Adolescents in the Emergency Department.

What adolescents say when they think about or attempt suicide influences the medical care they recei...

Aug 2015 26252868
Fuzzy Modeling to Predict Severely Depressed Left Ventricular Ejection Fraction following Admission to the Intensive Care Unit Using Clinical Physiology.

Left ventricular ejection fraction (LVEF) constitutes an important physiological parameter for the a...

Aug 2015 26345130
Changes in depression stigma after the Germanwings crash - Findings from German population surveys.

BACKGROUND: Media coverage of the Germanwings plane crash intensely focused on the co-pilot's mental...

Jul 2015 26254618
Perspectives on next steps in classification of oro-facial pain - part 1: role of ontology.

The purpose of this study was to review existing principles of oro-facial pain classifications and t...

Jul 2015 26212927
Machine learning algorithm accurately detects fMRI signature of vulnerability to major depression.

Standard functional magnetic resonance imaging (fMRI) analyses cannot assess the potential of a neur...

Jul 2015 26187550
Multivariate classification of autism spectrum disorder using frequency-specific resting-state functional connectivity--A multi-center study.

BACKGROUND: Resting-state functional magnetic resonance imaging studies examining low frequency fluc...

Jul 2015 26148789
Effects on Symptoms of Agitation and Depression in Persons With Dementia Participating in Robot-Assisted Activity: A Cluster-Randomized Controlled Trial.

OBJECTIVES: To examine effects on symptoms of agitation and depression in nursing home residents wit...

Jun 2015 26096582
Diagnostic Prediction for Social Anxiety Disorder via Multivariate Pattern Analysis of the Regional Homogeneity.

Although decades of efforts have been spent studying the pathogenesis of social anxiety disorder (SA...

Jun 2015 26180811
Using Gene Ontology to describe the role of the neurexin-neuroligin-SHANK complex in human, mouse and rat and its relevance to autism.

BACKGROUND: People with an autistic spectrum disorder (ASD) display a variety of characteristic beha...

Jun 2015 26047810
Prediction of remission in obsessive compulsive disorder using a novel machine learning strategy.

The study objective was to apply machine learning methodologies to identify predictors of remission ...

May 2015 25994109
PsyGeNET: a knowledge platform on psychiatric disorders and their genes.

UNLABELLED: PsyGeNET (Psychiatric disorders and Genes association NETwork) is a knowledge platform f...

May 2015 25964630
Predicting Methylphenidate Response in ADHD Using Machine Learning Approaches.

BACKGROUND: There are no objective, biological markers that can robustly predict methylphenidate res...

May 2015 25964505
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