Psychiatry

Evaluating generative AI responses to real-world drug-related questions.

Generative Artificial Intelligence (AI) systems such as OpenAI's ChatGPT, capable of an unprecedented ability to generate human-like text and converse in real time, hold potential for large-scale deployment in clinical settings such as substance use treatment. Treatment for substance use disorders (SUDs) is particularly high stakes, requiring evidence-based clinical treatment, mental health expert...

Predictive modelling of stress, anxiety and depression: A network analysis and machine learning study.

OBJECTIVE: This study assessed predictors of stress, anxiety and depression during the COVID-19 pandemic using a large number of demographic, COVID-19 context and psychological variables.

Enhancing Aviation Safety through AI-Driven Mental Health Management for Pilots and Air Traffic Controllers.

This article provides an overview of the mental health challenges faced by pilots and air traffic controllers (ATCs), whose stressful professional liv...

On new common fixed point theorems via bipolar fuzzy -metric space with their applications.

This research work is devoted to investigating new common fixed point theorems on bipolar fuzzy -metric space. Our main findings generalize some of th...

Three autism subtypes based on single-subject gray matter network revealed by semi-supervised machine learning.

Autism spectrum disorder (ASD) is a heterogeneous, early-onset neurodevelopmental condition characterized by persistent impairments in social interact...

Machine learning for antidepressant treatment selection in depression.

Finding the right antidepressant for the individual patient with major depressive disorder can be a difficult endeavor and is mostly based on trial-an...

Artificial intelligence in the era of planetary health: insights on its application for the climate change-mental health nexus in the Philippines.

This review explores the transformative potential of Artificial Intelligence (AI) in the light of evolving threats to planetary health, particularly t...

Network-based artificial intelligence approaches for advancing personalized psychiatry.

Psychiatric disorders have a complex biological underpinning likely involving an interplay of genetic and environmental risk contributions. Substantia...

Machine learning applied to the prediction of relapse, hospitalization, and suicide in bipolar disorder using neuroimaging and clinical data: A systematic review.

BACKGROUND: Bipolar disorder (BD) is associated with increased morbidity/mortality. Adverse outcome prediction might help with the management of patie...

Glycocalyx shedding patterns identifies antipsychotic-naïve patients with first-episode psychosis.

Psychotic disorders have been linked to immune-system abnormalities, increased inflammatory markers, and subtle neuroinflammation. Studies further sug...

Development of a differential treatment selection model for depression on consolidated and transformed clinical trial datasets.

Major depressive disorder (MDD) is the leading cause of disability worldwide, yet treatment selection still proceeds via "trial and error". Given the ...

Robots as Mental Health Coaches: A Study of Emotional Responses to Technology-Assisted Stress Management Tasks Using Physiological Signals.

The current study investigated the effectiveness of social robots in facilitating stress management interventions for university students by evaluatin...

A machine learning approach for differentiating bipolar disorder type II and borderline personality disorder using electroencephalography and cognitive abnormalities.

This study addresses the challenge of differentiating between bipolar disorder II (BD II) and borderline personality disorder (BPD), which is complica...

Predicting Depression, Anxiety, and Their Comorbidity among Patients with Breast Cancer in China Using Machine Learning: A Multisite Cross-Sectional Study.

Depression and anxiety are highly prevalent among patients with breast cancer. We tested the capacity of personal resources (psychological resilience,...

Predicting State-Level Firearm Suicide Rates: A Machine Learning Approach Using Public Policy Data.

INTRODUCTION: Over 40,000 people die by suicide annually in the U.S., and firearms are the most lethal suicide method. There is limited evidence on th...

Review of machine learning solutions for eating disorders.

BACKGROUND: Eating Disorders (EDs) are one of the most complex psychiatric disorders, with significant impairment of psychological and physical health...

Attention Analysis in Robotic-Assistive Therapy for Children With Autism.

Children with Autism Spectrum Disorder (ASD) show severe attention deficits, hindering their capacity to acquire new skills. The automatic assessment ...

Individual Predictors of Response to A Behavioral Activation-Based Digital Smoking Cessation Intervention: A Machine Learning Approach.

Depression is prevalent among individuals who smoke cigarettes and increases risk for relapse. A previous clinical trial suggests that Goal2Quit, a b...

Evaluation of future nurses' knowledge, attitudes and anxiety levels about artificial intelligence applications.

RATIONALE: Evaluating future nurses' perspectives on artificial intelligence, determining their missing or incorrect information on the subject and de...

Aberrant patterns of spontaneous brain activity in schizophrenia: A resting-state fMRI study and classification analysis.

BACKGROUND: Schizophrenia is a prevalent mental disorder, leading to severe disability. Currently, the absence of objective biomarkers hinders effecti...