Depression

Role of lactic acid-mediated ALKBH5 in depression induced by blue light exposure at night.

Artificial light at night (ALAN) has been classified as a significant environmental endocrine disrup...

Could sleep engineering be used to combat PTSD and depression?

Sleep engineering could be developed to provide a drug-free, non-invasive avenue to treat depression...

Co-Designed Mental Health Screening App (Here for You) for University Students: Pilot Feasibility Mixed Methods Study.

BACKGROUND: Mental health disorders are a growing public health concern among university students gl...

On the importance of white-box machine learning models in psychiatry: An example predicting suicidality in depression.

Identifying Transdiagnostic Predictors of Depression Across Psychoses: Informing Stratified Antidepressant Treatments.

INTRODUCTION: Depression frequently co-occurs with psychosis and is associated with poor outcomes. E...

Predicting Adolescent Response to School-Based Mindfulness: A Secondary Analysis of the MYRIAD Trial.

IMPORTANCE: Depression most commonly first emerges during adolescence, making early prevention criti...

Identifying past-year self-reported suicidality in outpatients with somatic symptom disorder using an interpretable machine-learning model: a multicenter study with an online calculator.

BACKGROUND: Somatic symptom disorder (SSD) is associated with an elevated risk of suicidality. Howev...

Differentiation between psychotic and non-psychotic major depression by the tabular prior-data fitted network.

BACKGROUND: Misdiagnosing psychotic major depression (PMD) as non-psychotic major depression (NPMD) ...

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

MDD-thinker: A reasoning-enhanced large language model for diagnosis of major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is a leading cause of global disability and poses a subs...

Discriminating between major depressive disorder and bipolar depression: Aberrant EEG microstate dynamics and machine learning classification.

BACKGROUND: Major depressive disorder (MDD) and bipolar depression (BD) are common mood disorders wi...

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...

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 ...

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

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

Predicting the need for electroconvulsive therapy via machine learning trained on electronic health record data.

OBJECTIVES: Electroconvulsive therapy (ECT) is an effective treatment of severe manifestations of me...

Accelerated brain aging in prolonged grief disorder of later life: Influence of comorbid depression.

BACKGROUND: Prolonged Grief Disorder (PGD) in later life may involve volumetric patterns indicative ...

Integrated AI-Driven Triage and Referral for Newcomer Mental Health in Ontario: Addressing Anxiety and Depression.

Systemic barriers, including language, navigation complexity, and long specialist wait-times, result...

Using AI to Train Future Clinicians in Depression Assessment: Feasibility Study.

BACKGROUND: Depression is a major global health care challenge, causing significant individual distr...

Evaluating an AI-Enabled Mobile Mental Health Monitoring Tool Among Family Caregivers of Adults Living With Cancer: Single-Arm Feasibility and Acceptability Trial Protocol.

BACKGROUND: Psychological distress, particularly symptoms of depression and anxiety (D&A), is highly...

Feasibility of machine learning classification of depression and anxiety symptoms among college students using 3D gait and sit-to-walk biomechanics.

BACKGROUND: Depression and anxiety are common and burdensome. Objective movement assessment may comp...