AIMC Topic: Depression

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Development of an explainable machine learning model for predicting depression in adolescent girls with non-suicidal self-injury: A cross-sectional multicenter study.

Journal of affective disorders
Non-suicidal self-injury (NSSI) in adolescent girls is a critical predictor of subsequent depression and suicide risk, yet current tools lack both accuracy and clinical interpretability. We developed the first explainable machine learning model integ...

Developing an interpretable machine learning model for screening depression in older adults with functional disability.

Journal of affective disorders
This study utilized data from the 2020 wave of the China Health and Retirement Longitudinal Study database, selecting 4322 participants aged 60 and above as the study sample. Important predictors of depression in older adults with functional disabili...

BERT and BERTopic for screening clinical depression on open-ended text messages collected through a mobile application from older adults.

BMC public health
BACKGROUND: Despite the high suicide rate in South Korea, older adults are reluctant to see a psychiatrist. Recently, text mining has gained popularity to detect depression in social media posts, but older adults rarely use social media. However, mor...

Deciphering Key Features of Social Resilience Versus Social Vulnerability in Later Life: A Biopsychosocial Model of Social Asymmetry.

The journals of gerontology. Series B, Psychological sciences and social sciences
OBJECTIVES: Confronted with shrinking social networks, older adults exhibit individual differences in social adaptability, reflected as socially resilient versus socially vulnerable. The purpose of this study was to examine key features that reflect ...

Predicting Stress, Anxiety, and Depression in Adult Men Based on Nutritional and Lifestyle Variables: A Comparative Analysis of Machine Learning Methods.

Journal of food science
Mental health disorders like depression, anxiety, and stress (DAS) are rising globally. Understanding how diet and lifestyle influence these conditions is vital for targeted interventions. This study explores the potential of machine learning (ML) to...

Question-based computational language approach outperform ratings scale in discriminating between anxiety and depression.

Journal of anxiety disorders
Major Depression (MD) and General Anxiety Disorder (GAD) are the most common mental health disorders, which typically are assessed quantitatively by rating scales such as PHQ-9 and GAD-7. However, recent advances in natural language processing (NLP) ...

Predictors of smartphone addiction in adolescents with depression: combing the machine learning and moderated mediation model approach.

Behaviour research and therapy
Smartphone addiction (SA) significantly impacts the physical and mental health of adolescents, and can further exacerbate existing mental health issues in those with depression. However, fewer studies have focused on the predictors of SA in adolescen...

On the State of NLP Approaches to Modeling Depression in Social Media: A Post-COVID-19 Outlook.

IEEE journal of biomedical and health informatics
Computational approaches to predicting mental health conditions in social media have been substantially explored in the past years. Multiple reviews have been published on this topic, providing the community with comprehensive accounts of the researc...

Discovery of Shared Latent Nonlinear Effective Connectivity for EEG-Based Depression Detection.

IEEE transactions on neural networks and learning systems
Granger causality (GC) effective connectivity (EC) calculated from electroencephalogram (EEG) signals has been widely used in mental disorder detection. However, the existing methods only take into account linear dynamics or nonlinear dynamics within...

Construction of a machine learning-based risk prediction model for depression in middle-aged and elderly patients with cardiovascular metabolic diseases in China: a longitudinal study.

BMC public health
BACKGROUND: The incidence of cardiovascular metabolic diseases (CMD) continues to rise among middle-aged and elderly populations, affecting not only physical health but also significantly increasing the risk of depression. This study aims to construc...