AIMC Topic: Depression

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Development of a short form of the Geriatric Depression Scale-30 based on item response theory and the RiskSLIM algorithm.

General hospital psychiatry Dec 25, 2024
Recently, methods of quickly and accurately screening for geriatric depression have attracted substantial attention. Short forms of the 30-item Geriatric Depression Scale have been developed based on classical test theory, such as the GDS-4, GDS-5, a...
Humans Machine Learning Algorithms Female Aged Magnetic Resonance Imaging Geriatric Assessment Gray Matter Aged, 80 and over Male Psychiatric Status Rating Scales Depression
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Momentary Depression Severity Prediction in Patients With Acute Depression Who Undergo Sleep Deprivation Therapy: Speech-Based Machine Learning Approach.

JMIR mental health Dec 23, 2024
BACKGROUND: Mobile devices for remote monitoring are inevitable tools to support treatment and patient care, especially in recurrent diseases such as major depressive disorder. The aim of this study was to learn if machine learning (ML) models based ...
Male Middle Aged Depressive Disorder, Major Severity of Illness Index Speech Depression Sleep Deprivation Humans Machine Learning Female Adult
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How do machine learning models perform in the detection of depression, anxiety, and stress among undergraduate students? A systematic review.

Cadernos de saude publica Dec 20, 2024
Undergraduate students are often impacted by depression, anxiety, and stress. In this context, machine learning may support mental health assessment. Based on the following research question: "How do machine learning models perform in the detection o...
Depression Humans Stress, Psychological Machine Learning Universities Students Anxiety
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Auxiliary identification of depression patients using interpretable machine learning models based on heart rate variability: a retrospective study.

BMC psychiatry Dec 18, 2024
OBJECTIVE: Depression has emerged as a global public health concern with high incidence and disability rates, which are timely imperative to identify and intervene in clinical practice. The objective of this study was to explore the association betwe...
Male Middle Aged Depression Support Vector Machine Machine Learning Retrospective Studies Female Adult Heart Rate Depressive Disorder Humans
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Screening for Depression and Anxiety Using a Nonverbal Working Memory Task in a Sample of Older Brazilians: Observational Study of Preliminary Artificial Intelligence Model Transferability.

JMIR formative research Dec 12, 2024
BACKGROUND: Anxiety and depression represent prevalent yet frequently undetected mental health concerns within the older population. The challenge of identifying these conditions presents an opportunity for artificial intelligence (AI)-driven, remote...
Depression Mass Screening Memory, Short-Term South American People Artificial Intelligence Female Male Humans Aged Middle Aged Aged, 80 and over Brazil Anxiety
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Predicting mental health treatment outcomes using latent growth mixture models and machine learning in a real-world clinical setting.

Journal of psychiatric research Dec 4, 2024
Previous models of depression outcomes have been limited by symptom heterogeneity within populations. This study conducted a retrospective analysis using latent growth mixture models to identify heterogeneous trajectories within a clinical population...
Retrospective Studies Female Reproducibility of Results Aged Humans Machine Learning Outpatients Patient Health Questionnaire Stress Disorders, Post-Traumatic ROC Curve United States Treatment Outcome Middle Aged Mental Health Services Aged, 80 and over Depression Area Under Curve Young Adult Latent Class Analysis Outcome Assessment, Health Care Adult Adolescent Veterans Male
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Using machine learning to predict the probability of incident 2-year depression in older adults with chronic diseases: a retrospective cohort study.

BMC psychiatry Dec 2, 2024
BACKGROUND: Older adults with chronic diseases are at higher risk of depressive symptoms than those without. For the onset of depressive symptoms, the prediction ability of changes in common risk factors over a 2-year follow-up period is unclear in t...
Retrospective Studies Female Risk Factors Aged Humans Depression Machine Learning Incidence Male Longitudinal Studies Middle Aged Chronic Disease Risk Assessment China
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STANet: A Novel Spatio-Temporal Aggregation Network for Depression Classification with Small and Unbalanced FMRI Data.

Tomography (Ann Arbor, Mich.) Nov 28, 2024
: Early diagnosis of depression is crucial for effective treatment and suicide prevention. Traditional methods rely on self-report questionnaires and clinical assessments, lacking objective biomarkers. Combining functional magnetic resonance imaging ...
Humans Female Depression Neural Networks, Computer Brain Magnetic Resonance Imaging Adult Male Deep Learning
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BPEN: Brain Posterior Evidential Network for trustworthy brain imaging analysis.

Neural networks : the official journal of the International Neural Network Society Nov 26, 2024
The application of deep learning techniques to analyze brain functional magnetic resonance imaging (fMRI) data has led to significant advancements in identifying prospective biomarkers associated with various clinical phenotypes and neurological cond...
Humans Alzheimer Disease Neural Networks, Computer Neuroimaging Uncertainty Deep Learning Brain Depression Female Cognitive Dysfunction Aged Magnetic Resonance Imaging Male
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The help-seeking process and predictors of mental health care use among individuals with depressive symptoms: a machine learning approach.

Frontiers in public health Nov 20, 2024
PURPOSE: The goal of the study was to identify the most important influences on professional healthcare use of people with depressive symptoms. We incorporated findings from research areas of health behaviors, stigma, and motivation to predict the he...
Help-Seeking Behavior Machine Learning Intention Middle Aged Female Humans Adult Depression Germany Male Surveys and Questionnaires Social Stigma Patient Acceptance of Health Care Mental Health Services
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