Latest AI and machine learning research in psychiatry for healthcare professionals.
This study explores the diagnostic value of dopamine system imaging characteristics in children with autism spectrum disorder. Functional magnetic resonance data from 551 children in the Autism Brain Imaging Data Exchange database were analyzed, focusing on six dopamine-related brain regions as regions of interest. Functional connectivity between these ROIs and across the whole brain was assessed....
More and more people are experiencing pressure from work, life, and education. These pressures often lead to an anxious state of mind, or even the early symptoms of suicidal ideation. With the advancement of artificial intelligence (AI) technology, large language models have become one of the most prominent technologies. They are often used for detecting psychological disorders. However, current...
In neuroscience, identifying distinct patterns linked to neurological disorders, such as Alzheimer's and Autism, is critical for early diagnosis and...
Feature selection is an important but challenging task in causal inference for obtaining unbiased estimates of causal quantities. Properly selected ...
Mental illness is a widespread and debilitating condition with substantial societal and personal costs. Traditional diagnostic and treatment approac...
Self Supervised Representation Learning (SSRepL) can capture meaningful and robust representations of the Attention Deficit Hyperactivity Disorder (...
Artificial intelligence and social computing rely on hundreds of thousands of content reviewers to classify high volumes of harmful and forbidden co...
Physical literacy is a multidimensional concept considered fundamental for lifelong participation in physical activity. Although theories on the relat...
Negative emotions such as loneliness, depression, and anxiety (LDA) are prevalent and pose significant challenges to emotional well-being. Traditional...
AIMS: This study aims of determine the mediating role of individual innovativeness in the effect of nursing students' artificial intelligence anxiety ...
Artificial intelligence (AI) has been increasingly used in delivering mental healthcare worldwide. Within this context, the traditional role of mental...
BACKGROUND: Literature on how to translate information extracted from clinical progress notes into numeric scores for 3-step theory of suicide (3ST) f...
OBJECTIVE: This study applied a machine-learning-based skill assessment system to investigate the association between supportive counseling skills (em...
OBJECTIVE: Current clinical evaluation may tend to lack precision in detecting depression in Parkinson's disease (DPD). Radiomics features have gradua...
INTRODUCTION: Dissociation is associated with clinical severity, increased risk of suicide and self-harm, and disproportionately affects adolescents a...
Speech production interferes with the measurement of changes in cardiac vagal activity during acute stress by attenuating the expected drop in heart r...
Sentiment analysis of patient feedback from the public health domain can aid decision makers in evaluating the provided services. The current paper ...
This study presents a narrative review of the use of digital health technologies (DHTs) and artificial intelligence to screen and mitigate risks and...
Vagus nerve stimulation (VNS) has emerged as a promising therapeutic intervention across various neurological and psychiatric conditions, including ...
This paper presents the very first attempt to evaluate machine learning fairness for depression detection using electroencephalogram (EEG) data. We ...