Depression

Speech-to-Speech Voice-Cloning Care (SVCC) for improving ICU-acquired anxiety for critically ill patients in a tertiary hospital in Beijing, China: protocol of a randomised, controlled trial.

INTRODUCTION: Intensive care unit (ICU) visiting restrictions in hospitals, implemented due to infection control and other factors, limited contact between patients and family members, affecting patients' well-being and clinical outcomes. With the evolution of voice-cloning based on artificial intelligence (AI) technology, it has become possible for health providers to communicate with critically ...

Discovery of suicide risk-associated predictors among emerging adults: an interpretable machine learning and network analysis approach.

Functional connectivity-based classification and subtyping of major depression for precision mental health: An ensemble graph neural network approach.

Major depressive disorder (MDD) remains clinically diagnosed based on subjective symptoms rather than objective neurobiological markers, which limits ...

Shift to the core: Abnormal core-periphery global topography in unipolar and bipolar depression.

This study explores the global signal topography of core and periphery brain networks in Major Depressive Disorder (MDD), Bipolar disorder (BD-Dep) an...

From linguistic analyses to large language models: A scoping review of methods used to investigate language features in depression research.

Clinicians have long relied on communication to identify mental states, as many mental health conditions manifest in language. This scoping review exa...

Non-suicidal self-injury in middle school students: Influencing factors and a risk prediction model.

Non-suicidal self-injury (NSSI) is becoming increasingly prevalent and harmful among adolescents, yet its intrinsic mechanism and early identification...

Differentiating unipolar and bipolar depression using multi-task eye-movement features.

BACKGROUND: Differentiating bipolar depression (BPD) from unipolar depression (UPD) is clinically challenging due to symptom overlap. This study explo...

Effective connectome-based predictive modeling reveals transdiagnostic heterogeneity of anhedonia from shared hubs to dissociable pathways.

Anhedonia, a core transdiagnostic symptom of psychiatric disorders, is commonly dissociated into anticipatory (AP) and consummatory (CP) components. H...

Temporal patterns and predictive factors of depressive disorders among adolescents and young people in Asia.

BACKGROUND: Depressive disorders are a leading cause of non-fatal health loss among adolescents and young adults, yet evidence on long-term trends and...

3DViT-GAT: a unified atlas-based 3D vision transformer and graph learning framework for major depressive disorder detection using structural MRI data.

Major depressive disorder (MDD) is a prevalent mental health condition that negatively impacts both individual well-being and global public health. Au...

Enhancing depression diagnosis with augmented brain signal driven decorrelated graph neural networks.

BACKGROUND: Major Depressive Disorder (MDD) is a leading global neuropsychiatric disorder, requiring precise diagnosis for effective intervention. Dev...

Factors associated with self-harm in patients with substance use disorders who died by suicide: national hybrid questionnaire registry study.

BACKGROUND: Self-harm, self-poisoning or self-injury, irrespective of the motivation, is a central risk factor for suicide. Still, there is limited kn...

Quantitative Histological Insights Into Sudden Arrhythmic Death Syndrome: Findings From a Forensic Autopsy Cohort.

Sudden arrhythmic death syndrome (SADS) is a major cause of sudden cardiac death in young individuals, characterized by structurally normal hearts and...

Using machine learning-based Natural Language Processing to quantify emergency department presentations related to suicide or self-harm in the Australian Capital Territory.

BACKGROUND: Suicide and self-harm are significant issues globally. Accurate, efficient and comprehensive data are required to identify people who pres...

An Interpretable Functional-Dynamic Synaptic Graph Neural Network for Major Depressive Disorder Diagnosis from rs-fMRI.

Major depressive disorder (MDD) is a serious, complex psychiatric condition that affects millions of people worldwide. Early diagnosis and biomarker i...

SAFEGUARD: Transforming Military Suicide Prevention Through Predictive Analytics and Targeted Interventions.

PURPOSE OF REVIEW: Machine learning predictive modeling can support scalable prevention of suicide-related behavior (SRB). SAFEGUARD is a three-pronge...

Predicting suicide attempts among the elderly: A machine learning evaluation of a staged ideation-to-action approach based on the Three-Step Theory.

Suicide among older adults remains a major global public health concern, particularly acute in South Korea. Effective prevention requires prediction m...

Multimodal Representation Learning for Parsing Biological Heterogeneity in Psychiatric Neuroimaging.

For decades, psychiatric neuroimaging has searched for biomarkers of depression and other disorders, but they remain elusive in clinical practice. Whi...

Harnessing exosomes for precision diagnostics and therapies in psychiatry disorders.

Exosomes are nanosized extracellular vesicles enriched with proteins, lipids, and nucleic acids and are emerging as powerful mediators of intercellula...

Ethical challenges of using artificial intelligence in suicide prevention: a literature review.

Artificial intelligence (AI) is a tool that could provide useful prevention strategies for people at risk of suicide. However, there are many ethical ...