Psychiatry

Prediction of Sex-Specific Suicide Risk Using Machine Learning and Single-Payer Health Care Registry Data From Denmark.

IMPORTANCE: Suicide is a public health problem, with multiple causes that are poorly understood. The...

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...

Addressing the Credit Assignment Problem in Treatment Outcome Prediction using Temporal Difference Learning.

Mental health patients often undergo a variety of treatments before finding an effective one. Improv...

Targeted prescription of cognitive-behavioral therapy versus person-centered counseling for depression using a machine learning approach.

OBJECTIVE: Depression is a highly common mental disorder and a major cause of disability worldwide. ...

Personalized prognostic prediction of treatment outcome for depressed patients in a naturalistic psychiatric hospital setting: A comparison of machine learning approaches.

OBJECTIVE: Research on predictors of treatment outcome in depression has largely derived from random...

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 (...

[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...

[Theoretical Review of Robot Anxiety].

The aim of the study is to describe the effect of robot anxiety. The forming of the concept and the ...

Changes in Functional Connectivity Predict Outcome of Repetitive Transcranial Magnetic Stimulation Treatment of Major Depressive Disorder.

Repetitive transcranial magnetic stimulation (rTMS) treatment of major depressive disorder (MDD) is ...

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...

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 di...

What health records data are required for accurate prediction of suicidal behavior?

OBJECTIVE: The study sought to evaluate how availability of different types of health records data a...

A computational study of mental health awareness campaigns on social media.

As public discourse continues to progress online, it is important for mental health advocates, publi...

Predicting post-experiment fatigue among healthy young adults: Random forest regression analysis.

The current study utilized a random forest regression analysis to predict post-experiment fatigue in...

Applying Natural Language Processing to Evaluate News Media Coverage of Bullying and Cyberbullying.

Bullying events have frequently been the focus of coverage by news media, including news stories abo...

The Language of LGBTQ+ Minority Stress Experiences on Social Media.

LGBTQ+ (lesbian, gay, bisexual, transgender, queer) individuals are at significantly higher risk for...

Machine learning technique reveals intrinsic characteristics of schizophrenia: an alternative method.

Machine learning technique has long been utilized to assist disease diagnosis, increasing clinical p...

Leveraging Digital Health and Machine Learning Toward Reducing Suicide-From Panacea to Practical Tool.

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 ...

Elucidating Compound Mechanism of Action and Predicting Cytotoxicity Using Machine Learning Approaches, Taking Prediction Confidence into Account.

The modes of action (MoAs) of drugs frequently are unknown, because many are small molecules initial...

Identification and evaluation of cognitive deficits in schizophrenia using "Machine learning".

BACKGROUND: Schizophrenia can be interpreted as a pathology involving the neocortex whose cognitive ...