Psychiatry

Depression

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

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Showing 253-273 of 1,353 articles
Real-time assistance in suicide prevention helplines using a deep learning-based recommender system: A randomized controlled trial.

OBJECTIVE: To evaluate the effectiveness and usability of an AI-assisted tool in providing real-time...

Predicting drug craving among ketamine-dependent users through machine learning based on brain structural measures.

BACKGROUND: Craving is a core factor driving drug-seeking and -taking, representing a significant ri...

Enhancing suicidal behavior detection in EHRs: A multi-label NLP framework with transformer models and semantic retrieval-based annotation.

BACKGROUND: Suicide is a leading cause of death worldwide, making early identification of suicidal b...

Using machine learning to predict the probability of incident 2-year depression in older adults with chronic diseases: a retrospective cohort study.

BACKGROUND: Older adults with chronic diseases are at higher risk of depressive symptoms than those ...

STANet: A Novel Spatio-Temporal Aggregation Network for Depression Classification with Small and Unbalanced FMRI Data.

: Early diagnosis of depression is crucial for effective treatment and suicide prevention. Tradition...

Exploring new scientific innovations in combating suicide: a stress detection wristband.

There is a silent pandemic of suicides around the world, with an exponential increase in suicidality...

The efficacy of topological properties of functional brain networks in identifying major depressive disorder.

Major Depressive Disorder (MDD) is a common mental disorder characterized by cognitive impairment, a...

Current update on the neurological manifestations of long COVID: more questions than answers.

Since the outbreak of the COVID-19 pandemic, there has been a global surge in patients presenting wi...

BPEN: Brain Posterior Evidential Network for trustworthy brain imaging analysis.

The application of deep learning techniques to analyze brain functional magnetic resonance imaging (...

Disentangling the Genetic Landscape of Peripartum Depression: A Multi-Polygenic Machine Learning Approach on an Italian Sample.

BACKGROUND: The genetic determinants of peripartum depression (PPD) are not fully understood. Using ...

Predicting suicidal behavior outcomes: an analysis of key factors and machine learning models.

BACKGROUND: Suicidal behaviors, which may lead to death (suicide) or survival (suicide attempt), are...

An adaptive multi-graph neural network with multimodal feature fusion learning for MDD detection.

Major Depressive Disorder (MDD) is an affective disorder that can lead to persistent sadness and a d...

The voice of depression: speech features as biomarkers for major depressive disorder.

BACKGROUND: Psychiatry faces a challenge due to the lack of objective biomarkers, as current assessm...

Speech based suicide risk recognition for crisis intervention hotlines using explainable multi-task learning.

BACKGROUND: Crisis Intervention Hotline can effectively reduce suicide risk, but suffer from low con...

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