Depression

A Controlled Trial Using Natural Language Processing to Examine the Language of Suicidal Adolescents in the Emergency Department.

What adolescents say when they think about or attempt suicide influences the medical care they receive. Mental health professionals use teenagers' words, actions, and gestures to gain insight into their emotional state and to prescribe what they believe to be optimal care. This prescription is often inconsistent among caregivers, however, and leads to varying outcomes. This variation could be redu...

Changes in depression stigma after the Germanwings crash - Findings from German population surveys.

BACKGROUND: Media coverage of the Germanwings plane crash intensely focused on the co-pilot's mental illness and was criticized for potentially increasing depression stigma. We explored whether stigma beliefs towards persons with depression changed in April 2015 (about one month after the crash) compared to 2014.

Machine learning algorithm accurately detects fMRI signature of vulnerability to major depression.

Standard functional magnetic resonance imaging (fMRI) analyses cannot assess the potential of a neuroimaging signature as a biomarker to predict indiv...

Effects on Symptoms of Agitation and Depression in Persons With Dementia Participating in Robot-Assisted Activity: A Cluster-Randomized Controlled Trial.

OBJECTIVES: To examine effects on symptoms of agitation and depression in nursing home residents with moderate to severe dementia participating in a r...

PsyGeNET: a knowledge platform on psychiatric disorders and their genes.

UNLABELLED: PsyGeNET (Psychiatric disorders and Genes association NETwork) is a knowledge platform for the exploratory analysis of psychiatric disease...

Negative Affect Instability among Individuals with Comorbid Borderline Personality Disorder and Posttraumatic Stress Disorder.

Ecological momentary assessment (EMA; Stone & Shiffman, 1994) was utilized to examine affective instability (AI) in the daily lives of outpatients wit...

Screening Internet forum participants for depression symptoms by assembling and enhancing multiple NLP methods.

Depression is a disease that can dramatically lower quality of life. Symptoms of depression can range from temporary sadness to suicide. Embarrassment...

A Mobile Health Application to Predict Postpartum Depression Based on Machine Learning.

BACKGROUND: Postpartum depression (PPD) is a disorder that often goes undiagnosed. The development of a screening program requires considerable and ca...

Machine learning approaches for integrating clinical and imaging features in late-life depression classification and response prediction.

OBJECTIVE: Currently, depression diagnosis relies primarily on behavioral symptoms and signs, and treatment is guided by trial and error instead of ev...

Spontaneous motion on two-dimensional continuous attractors.

Attractor models are simplified models used to describe the dynamics of firing rate profiles of a pool of neurons. The firing rate profile, or the neu...

Using support vector machines to identify protein phosphorylation sites in viruses.

Phosphorylation of viral proteins plays important roles in enhancing replication and inhibition of normal host-cell functions. Given its importance in...

Feature Selection and Classification of Electroencephalographic Signals: An Artificial Neural Network and Genetic Algorithm Based Approach.

Feature selection is an important step in many pattern recognition systems aiming to overcome the so-called curse of dimensionality. In this study, an...

Interpretable Symptom Vectors for Depression in a Large Language Model

Patients with depression present with diverse symptom profiles, yet clinical practice routinely reduces this variation to a single severity score. Lar...

SMOTE-VAR: An Uncertainty-Aware Oversampling Method for Predicting Depression Remission in University Students

University students experience disproportionately high rates of common mental health conditions, such as depression, which can impair learning, social...

TAMI: Temporally Aligned, Missingness-Aware, and Interpretable Multimodal Fusion for Mental Health Assessment in Older Adults with Mild Cognitive Impairment

Depression and anxiety in older adults with Mild Cognitive Impairment (MCI) are frequently underdiagnosed due to limited access to care. Multimodal an...

SAGE: Stability-Aware Graph-Based Ensemble Feature Selection for Explainable Postpartum Depression Risk Prediction

Postpartum depression (PPD) poses a major burden on maternal and child health, especially in low- and middle-income countries where prevalence exceeds...

Seeking Help from Chatbots for Suicide Thoughts: Associations with Other Help Seeking Sources and Mental Health Symptoms

Background: Generative AI is evolving at a rapid pace, and many individuals are utilizing chatbots for mental health support. The safety of chatbots a...

Making Broad Evidence Synthesis Feasible: An LLM Screening Agent for Meta-Analyses Applied To Suicide Prevention

Importance. Systematic reviews and meta-analyses inform suicide-prevention policy and practice, but broad database searches are difficult to screen ma...

NeuroAid An Open-Data Multimodal Screening Framework for Parkinson's and Depression Risk Estimation

Neurological and mental-health conditions such as Parkinson's disease (PD) and major depressive disorder (MDD) impose a substantial and growing global...

Wearable Prompt: In-Context Learning for Depression and Anxiety Prediction from Consumer Smart Ring Metrics

Large language models provide a promising framework for wearable-based health prediction by converting structured physiological and behavioral measure...