Psychiatry

Depression

Latest AI and machine learning research in depression for healthcare professionals.

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Showing 190-210 of 1,353 articles
Identifying major depressive disorder among US adults living alone using stacked ensemble machine learning algorithms.

BACKGROUND: It has been increasingly recognized that adults living alone have a higher likelihood of...

Prediction of depressive disorder using machine learning approaches: findings from the NHANES.

BACKGROUND: Depressive disorder, particularly major depressive disorder (MDD), significantly impact ...

Differentiating adolescent suicidal and nonsuicidal self-harm with artificial intelligence: Beyond suicidal intent and capability for suicide.

Clinical differentiation between adolescent suicidal self-harm (SSH) and nonsuicidal self-harm (NSSH...

EEG Temporal-Spatial Feature Learning for Automated Selection of Stimulus Parameters in Electroconvulsive Therapy.

The risk of adverse effects in Electroconvulsive Therapy (ECT), such as cognitive impairment, can be...

Predictors of depression among Chinese college students: a machine learning approach.

BACKGROUND: Depression is highly prevalent among college students, posing a significant public healt...

Emotional stimulated speech-based assisted early diagnosis of depressive disorders using personality-enhanced deep learning.

BACKGROUND: Early diagnosis of depression is crucial, and speech-based early diagnosis of depression...

M₂DC: A Meta-Learning Framework for Generalizable Diagnostic Classification of Major Depressive Disorder.

Psychiatric diseases are bringing heavy burdens for both individual health and social stability. The...

A machine learning model using clinical notes to estimate PHQ-9 symptom severity scores in depressed patients.

BACKGROUND: Lack of widespread use of the Patient Health Questionnaire 9-item (PHQ-9) in clinical pr...

AFMDD: Analyzing Functional Connectivity Feature of Major Depressive Disorder by Graph Neural Network-Based Model.

The extraction of biomarkers from functional connectivity (FC) in the brain is of great significance...

Using natural language processing to identify patterns associated with depression, anxiety, and stress symptoms during the COVID-19 pandemic.

BACKGROUND: Combining data-driven natural language processing techniques with traditional methods us...

Machine Learning Tool for New Selective Serotonin and Serotonin-Norepinephrine Reuptake Inhibitors.

Depression, a serious mood disorder, affects about 5% of the population. Currently, there are two gr...

Interventions to improve medication adherence in persons with mental disorders.

PURPOSE OF REVIEW: Nonadherence to medication is prevalent in patients with mental illness. Various ...

An Explainable Artificial Intelligence Text Classifier for Suicidality Prediction in Youth Crisis Text Line Users: Development and Validation Study.

BACKGROUND: Suicide represents a critical public health concern, and machine learning (ML) models of...

Evaluation of an AI-Based Voice Biomarker Tool to Detect Signals Consistent With Moderate to Severe Depression.

PURPOSE: Mental health screening is recommended by the US Preventive Services Task Force for all pat...

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