Psychiatry

Depression

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

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The Goldilocks Zone: Finding the right balance of user and institutional risk for suicide-related generative AI queries.

Generative artificial intelligence (genAI) has potential to improve healthcare by reducing clinician...

A Plasma Proteomics-Based Model for Identifying the Risk of Postpartum Depression Using Machine Learning.

Postpartum depression (PPD) poses significant risks to maternal and infant health, yet proteomic ana...

Prediction of late-onset depression in the elderly Korean population using machine learning algorithms.

Late-onset depression (LOD) refers to depression that newly appears in elderly individuals without p...

Machine learning algorithms to predict depression in older adults in China: a cross-sectional study.

OBJECTIVE: The 2-fold objective of this research is to investigate machine learning's (ML) predictiv...

Beyond the hot flashes: how machine learning is uncovering the complexity of menopause-related depression.

BACKGROUND: The transition into menopause marks a significant stage in a woman's life, indicating th...

A Longitudinal Prediction of Suicide Attempts in Borderline Personality Disorder: A Machine Learning Study.

Borderline personality disorder (BPD) is associated with a high risk of suicide. Despite several ris...

Analysis of User-Generated Posts on Social Media of Adjuvant Analgesics: A Machine Learning Study.

Antiepileptics and antidepressants are frequently prescribed for chronic pain, but their efficacy a...

Evaluating of BERT-based and Large Language Mod for Suicide Detection, Prevention, and Risk Assessment: A Systematic Review.

Suicide constitutes a public health issue of major concern. Ongoing progress in the field of artific...

Utilising AI technique to identify depression risk among doctoral students.

The phenomenon that the depression risk among doctoral students is higher than that of other groups ...

Diagnosis of major depressive disorder using a novel interpretable GCN model based on resting state fMRI.

The diagnosis and analysis of major depressive disorder (MDD) faces some intractable challenges such...

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

Recently, methods of quickly and accurately screening for geriatric depression have attracted substa...

How do machine learning models perform in the detection of depression, anxiety, and stress among undergraduate students? A systematic review.

Undergraduate students are often impacted by depression, anxiety, and stress. In this context, machi...

Auxiliary identification of depression patients using interpretable machine learning models based on heart rate variability: a retrospective study.

OBJECTIVE: Depression has emerged as a global public health concern with high incidence and disabili...

Comparison between clinician and machine learning prediction in a randomized controlled trial for nonsuicidal self-injury.

BACKGROUND: Nonsuicidal self-injury is a common health problem in adolescents and associated with fu...

Evaluating virtual reality technology in psychotherapy: impacts on anxiety, depression, and ADHD.

BACKGROUND: Mental health issues pose a significant challenge for medical providers and the general ...

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