Psychiatry

Predictors of suicide ideation among South Korean adolescents: A machine learning approach.

BACKGROUND: The current study developed a predictive model for suicide ideation among South Korean (Korean) adolescents using a comprehensive set of factors across demographic, physical and mental health, academic, social, and behavioral domains. The aim of this study was to address the pressing public health concerns of adolescent suicide in Korea and the methodological limitations of suicidal re...

Uncovering psychiatric phenotypes using unsupervised machine learning: A data-driven symptoms approach.

BACKGROUND: Current categorical classification systems of psychiatric diagnoses lead to heterogeneity of symptoms within disorders and common co-occurrence of disorders. We investigated the heterogeneous and overlapping nature of symptom endorsement in a population-based sample across three of the most common categories of psychiatric disorders: depressive disorders, anxiety disorders, and sleep-w...

Identifying suicide attempts, ideation, and non-ideation in major depressive disorder from structural MRI data using deep learning.

The present study aims to identify suicide risks in major depressive disorders (MDD) patients from structural MRI (sMRI) data using deep learning. In ...

Artificial intelligence (AI) and machine learning (ML) based decision support systems in mental health: An integrative review.

An integrative review investigating the incorporation of artificial intelligence (AI) and machine learning (ML) based decision support systems in ment...

Cross Dataset Analysis for Generalizability of HRV-Based Stress Detection Models.

Stress is an increasingly prevalent mental health condition across the world. In Europe, for example, stress is considered one of the most common heal...

Effects of a cognitive-based intervention program using social robot PIO on cognitive function, depression, loneliness, and quality of life of older adults living alone.

OBJECTIVE: Social robot interventions are being implemented to reduce cognitive decline, depression, and loneliness among older adults. However, the t...

User Feedback on the Use of a Natural Language Processing Application to Screen for Suicide Risk in the Emergency Department.

Suicide is the 10th leading cause of death in the USA and globally. Despite decades of research, the ability to predict who will die by suicide is sti...

Cognitive Depression Detection Cyber-Medical System Based on EEG Analysis and Deep Learning Approaches.

Long-term depression and negative emotional cycles affect life quality and work productivity. However, depression is not easy to detect, with current ...

EEG emotion recognition using improved graph neural network with channel selection.

BACKGROUND AND OBJECTIVE: Emotion classification tasks based on electroencephalography (EEG) are an essential part of artificial intelligence, with pr...

Understanding and detecting behaviours prior to a suicide attempt: A mixed-methods study.

OBJECTIVE: Prior research suggests there are observable behaviours preceding suicide attempts in public places. However, there are currently no ways t...

The assistance of BAZAR robot promotes improved upper limb motor coordination in workers performing an actual use-case manual material handling.

This study aims at evaluating upper limb muscle coordination and activation in workers performing an actual use-case manual material handling (MMH). T...

PRA-Net: Part-and-Relation Attention Network for depression recognition from facial expression.

Artificial intelligence methods are widely applied to depression recognition and provide an objective solution. Many effective automated methods for d...

Effect of robot-assisted gait training on quality of life and depression in neurological impairment: A systematic review and meta-analysis.

OBJECTIVE: Robot-assisted gait training (RAGT) is often used as a rehabilitation tool for neurological impairments. The purpose of this study is to in...

Computing personalized brain functional networks from fMRI using self-supervised deep learning.

A novel self-supervised deep learning (DL) method is developed to compute personalized brain functional networks (FNs) for characterizing brain functi...

Predicting dropout from psychological treatment using different machine learning algorithms, resampling methods, and sample sizes.

The occurrence of dropout from psychological interventions is associated with poor treatment outcome and high health, societal and economic costs. Re...

Qualitative and Artificial Intelligence-based Sentiment Analyses of Anti-LGBTI+ Hate Speech on Twitter in Turkey.

The aim of this study was to evaluate hate speech in Turkish LGBTI+-related tweets during a one-month period of artificial intelligence-based sentimen...

Wearable Artificial Intelligence for Anxiety and Depression: Scoping Review.

BACKGROUND: Anxiety and depression are the most common mental disorders worldwide. Owing to the lack of psychiatrists around the world, the incorporat...

Classification of Depression and Its Severity Based on Multiple Audio Features Using a Graphical Convolutional Neural Network.

Audio features are physical features that reflect single or complex coordinated movements in the vocal organs. Hence, in speech-based automatic depres...

Review of Machine Learning and Artificial Intelligence (ML/AI) for the Pediatric Neurologist.

Artificial intelligence (AI) and a popular branch of AI known as machine learning (ML) are increasingly being utilized in medicine and to inform medic...

Application of Natural Language Processing (NLP) in Detecting and Preventing Suicide Ideation: A Systematic Review.

(1) Introduction: Around a million people are reported to die by suicide every year, and due to the stigma associated with the nature of the death, th...