Psychiatry

Modeling the empathy-self-discovery paradox in Gen Z social behavior with NPD using artificial neural networks.

This study investigates the resurgence of the Myers-Briggs Type Indicator (MBTI) among Generation Z,...

Integrating qHTS and QSAR Models to Identify Safe GPCR-Targeted Compounds: A Focus on hERG-Dependent Cardiotoxicity.

G-protein-coupled receptors (GPCRs) are a diverse family of seven-transmembrane domain receptors tha...

Heterophily-Aware Spectral GCN for Population-Level Brain Disorder Prediction.

Integrating resting-state functional magnetic resonance imaging (rs-fMRI) and phenotypic data is a p...

Threat discrimination of real-world social interactions in schizotypal traits.

Threat detection is compromised across the schizophrenia spectrum, often revealed by paranoia and de...

Peripheral blood transcriptomic biomarkers for predicting antidepressant response in major depressive disorder.

Digital companionship: The interplay of conversational AI, loneliness, social anxiety, and quality of life among young adults.

This study examines the relationship between Conversational Artificial Intelligence (CAI) usage and ...

Predicting fine motor deficit in autism by measuring brain activities and characterizing motor impairments.

Motor impairments affect approximately 86.9% of children with Autism Spectrum Disorder (ASD), often ...

Psychotherapists versus artificial intelligence: let's not raise the white flag.

Early detection of adults ADHD using electronic health records: A machine learning study.

Multistage Electrocardiographic Profiling for Mental Stress-Induced Myocardial Ischemia in Women: A Prospective, Age-Matched Cohort Study in China.

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with...

Young academic psychiatrists in 2050s: future directions across low- and high-income settings.

Academic psychiatrists inhabit two professional identities: clinician and researcher. In some settin...

Temporomandibular Disorders Diagnosis: Current Challenges and the Promising Role of Artificial Intelligence.

Temporomandibular disorders (TMDs) are a group of musculoskeletal and joint-related conditions affec...

Leveraging Machine Learning to Uncover Ethnic-Specific Predictors of Maternal Postpartum Depression.

Maternal postpartum depression (PPD) is a significant mental health issue that affects over 15% of m...

Leveraging machine learning to identify gendered stereotypes and body image concerns on diet and fitness online forums.

The pervasive expectations about ideal body types in Western society can lead to body image concerns...

A machine learning approach to predicting clinical trajectories in bipolar disorder.

BACKGROUND: Bipolar disorder (BD) is characterized by significant heterogeneity in clinical presenta...

Identification and experimental confirmation of TBC1D10C as a shared transcriptional link between abdominal aortic aneurysm and major depressive disorder.

BACKGROUND: Abdominal aortic aneurysm (AAA) and major depressive disorder (MDD) are prevalent condit...

Prevalence and factors associated with suicidal ideation based on the Malaysia National Health and Morbidity Survey: A machine learning analysis.

BACKGROUND: This study estimated the prevalence of past-two-week suicidal ideation and examined its ...

Expanding the horizon of oculomics: A narrative review on the emerging roles of the anterior segment and mobile health.

Oculomics uses the eye to gain insights into systemic health. Although initially focused on retinal ...

Artificial intelligence and mental health in the workplace: positive and negative impacts.

The mental health of workers is a crucial objective of occupational health and safety programs. Ment...

Deep learning for psychiatric genomics: from tools to applications.

The genetic architecture of psychiatric disorders is highly complex, with genome-wide association st...

Dexpression recognition from EEG based on nonlinear analysis and adaptive feature fusion.

Machine learning techniques have recently shown significant promise in electroencephalograph (EEG)-b...