Psychiatry

Neural Networks in Neurological and Psychiatric Diseases.

Outgroup Machine Learning Approach Identifies Single Nucleotide Variants in Noncoding DNA Associated with Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a heritable neurodevelopmental disorder affecting 1 in 59 children...

[Artificial Intelligence in Psychiatry].

Diagnosis of psychiatric disorders is based primarily on subjective symptoms, and neuroimaging or ot...

Roles, Strengths and Challenges of Using Robots in Interventions for Children with Autism Spectrum Disorder (ASD).

The aim of this research was to study roles, strengths and challenges of robot-mediated intervention...

Brain Age in Early Stages of Bipolar Disorders or Schizophrenia.

BACKGROUND: The greater presence of neurodevelopmental antecedants may differentiate schizophrenia f...

Machine learning for psychiatric patient triaging: an investigation of cascading classifiers.

OBJECTIVE: Develop an approach, One-class-at-a-time, for triaging psychiatric patients using machine...

ICT and autism care: state of the art.

PURPOSE OF REVIEW: Over the past 10 years, the use of information and communication technologies (IC...

Small-Group Technology-Assisted Instruction: Virtual Teacher and Robot Peer for Individuals with Autism Spectrum Disorder.

The authors combined virtual reality technology and social robotics to develop a tutoring system tha...

Technology in geriatrics.

Recently, the interest of industry, government agencies and healthcare professionals in technology f...

In-home Robots Improve Social Skills in Children With Autism.

The impact of social housing on mental health: longitudinal analyses using marginal structural models and machine learning-generated weights.

BACKGROUND: Social housing may provide an affordable and secure residential environment, but has als...

Rise of the machines? Machine learning approaches and mental health: opportunities and challenges.

Machine learning methods are being increasingly applied to physical healthcare. In this article we d...

Use of Machine Learning to Determine Deviance in Neuroanatomical Maturity Associated With Future Psychosis in Youths at Clinically High Risk.

IMPORTANCE: Altered neurodevelopmental trajectories are thought to reflect heterogeneity in the path...

Will Machine Learning Enable Us to Finally Cut the Gordian Knot of Schizophrenia.

Multivariate Pattern Analysis of Genotype-Phenotype Relationships in Schizophrenia.

Genetic risk variants for schizophrenia have been linked to many related clinical and biological phe...

Brain Subtyping Enhances The Neuroanatomical Discrimination of Schizophrenia.

Identifying distinctive subtypes of schizophrenia could ultimately enhance diagnostic and prognostic...

Disease Definition for Schizophrenia by Functional Connectivity Using Radiomics Strategy.

Specific biomarker reflecting neurobiological substrates of schizophrenia (SZ) is required for its d...

Multisite Machine Learning Analysis Provides a Robust Structural Imaging Signature of Schizophrenia Detectable Across Diverse Patient Populations and Within Individuals.

Past work on relatively small, single-site studies using regional volumetry, and more recently machi...

Predicting Response to Repetitive Transcranial Magnetic Stimulation in Patients With Schizophrenia Using Structural Magnetic Resonance Imaging: A Multisite Machine Learning Analysis.

BACKGROUND: The variability of responses to plasticity-inducing repetitive transcranial magnetic sti...

Factors associated with viral suppression among HIV-positive Kenyan gay and bisexual men who have sex with men.

The UNAIDS 90-90-90 target has prioritized achieving high rates of viral suppression. We identified ...

Predictive markers of depression in hypertension.

Hypertension and depression, as 2 major public health issues, are closely related. For patients havi...