Psychiatry

Using heart rate profiles during sleep as a biomarker of depression.

BACKGROUND: Abnormalities in heart rate during sleep linked to impaired neuro-cardiac modulation may...

Prediction models for high risk of suicide in Korean adolescents using machine learning techniques.

OBJECTIVE: Suicide in adolescents is a major problem worldwide and previous history of suicide ideat...

SynGO: An Evidence-Based, Expert-Curated Knowledge Base for the Synapse.

Synapses are fundamental information-processing units of the brain, and synaptic dysregulation is ce...

Machine learning identifies unaffected first-degree relatives with functional network patterns and cognitive impairment similar to those of schizophrenia patients.

Schizophrenia (SCZ) patients and their unaffected first-degree relatives (FDRs) share similar functi...

Prediction of rTMS treatment response in major depressive disorder using machine learning techniques and nonlinear features of EEG signal.

BACKGROUND: Prediction of therapeutic outcome of repetitive transcranial magnetic stimulation (rTMS)...

Diagnosis of Human Psychological Disorders using Supervised Learning and Nature-Inspired Computing Techniques: A Meta-Analysis.

A psychological disorder is a mutilation state of the body that intervenes the imperative functionin...

Deep Sequential Models for Suicidal Ideation From Multiple Source Data.

This paper presents a novel method for predicting suicidal ideation from electronic health records (...

Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk.

We address the challenge of detecting the contribution of noncoding mutations to disease with a deep...

See your mental state from your walk: Recognizing anxiety and depression through Kinect-recorded gait data.

As the challenge of mental health problems such as anxiety and depression increasing today, more con...

Real-time analysis of the behaviour of groups of mice via a depth-sensing camera and machine learning.

Preclinical studies of psychiatric disorders use animal models to investigate the impact of environm...

Identifying psychosis spectrum disorder from experience sampling data using machine learning approaches.

The ubiquity of smartphones opened up the possibility of widespread use of the Experience Sampling M...

nCREANN: Nonlinear Causal Relationship Estimation by Artificial Neural Network; Applied for Autism Connectivity Study.

Quantifying causal (effective) interactions between different brain regions are very important in ne...

Identification and analysis of behavioral phenotypes in autism spectrum disorder via unsupervised machine learning.

BACKGROUND AND OBJECTIVE: Autism spectrum disorder (ASD) is a heterogeneous disorder. Research has e...

Artificial Intelligence based facial recognition for Mood Charting among men on life style modification and it's correlation with cortisol.

UNLABELLED: Today, clinicians and researchers believe that mood disorders in children and adolescent...

Psychosocial Health Interventions by Social Robots: Systematic Review of Randomized Controlled Trials.

BACKGROUND: Social robots that can communicate and interact with people offer exciting opportunities...

Your Robot Therapist Will See You Now: Ethical Implications of Embodied Artificial Intelligence in Psychiatry, Psychology, and Psychotherapy.

BACKGROUND: Research in embodied artificial intelligence (AI) has increasing clinical relevance for ...

Proactive Suicide Prevention Online (PSPO): Machine Identification and Crisis Management for Chinese Social Media Users With Suicidal Thoughts and Behaviors.

BACKGROUND: Suicide is a great public health challenge. Two hundred million people attempt suicide i...

Detecting depression using a framework combining deep multimodal neural networks with a purpose-built automated evaluation.

Machine learning (ML) has been introduced into the medical field as a means to provide diagnostic to...

Comedic experience with two robots aided a child with autism spectrum disorder to realize the importance of nonverbal communication.

Assessing cognitive mental workload via EEG signals and an ensemble deep learning classifier based on denoising autoencoders.

To estimate the reliability and cognitive states of operator performance in a human-machine collabor...

Giving Voice to Vulnerable Children: Machine Learning Analysis of Speech Detects Anxiety and Depression in Early Childhood.

Childhood anxiety and depression often go undiagnosed. If left untreated these conditions, collectiv...