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Showing 1576-1596 of 1,939 articles

Population-Wide Depression Incidence Forecasting Comparing Autoregressive Integrated Moving Average and Vector Autoregressive Integrated Moving Average to Temporal Fusion Transformers: Longitudinal Observational Study.

BACKGROUND: Accurate prediction of population-wide depression incidence is vital for effective publi...

May 2025 40354111

Reasoning language models for more transparent prediction of suicide risk.

BACKGROUND: We previously demonstrated that a large language model could estimate suicide risk using...

May 2025 40350181

Voice biomarkers of perinatal depression: cross-sectional nationwide pilot study report

Perinatal depression (PND) affects 1 in 5 mothers, with 85% lacking support. Digital health tools ...

May 2025 http://arxiv.org/abs/2505.06412v1

Construction and validation of a predictive model for suicidal ideation in non-psychiatric elderly inpatients.

BACKGROUND: Suicide poses a substantial public health challenge globally, with the elderly populatio...

(1)

May 2025 40346469

Fair Uncertainty Quantification for Depression Prediction

Trustworthy depression prediction based on deep learning, incorporating both predictive reliabilit...

May 2025 http://arxiv.org/abs/2505.04931v1

Predicting peripartum depression using elastic net regression and machine learning: the role of remnant cholesterol.

BACKGROUND: Traditional statistical methods have dominated research on peripartum depression (PPD), ...

(1)

May 2025 40340559

Identifying most important predictors for suicidal thoughts and behaviours among healthcare workers active during the Spain COVID-19 pandemic: a machine-learning approach.

AIMS: Studies conducted during the COVID-19 pandemic found high occurrence of suicidal thoughts and ...

May 2025 40340775

A Deep Learning approach for Depressive Symptoms assessment in Parkinson's disease patients using facial videos

Parkinson's disease (PD) is a neurodegenerative disorder, manifesting with motor and non-motor sym...

May 2025 http://arxiv.org/abs/2505.03845v1

An Explainable Anomaly Detection Framework for Monitoring Depression and Anxiety Using Consumer Wearable Devices

Continuous monitoring of behavior and physiology via wearable devices offers a novel, objective me...

May 2025 http://arxiv.org/abs/2505.03039v1

Accuracy of Machine Learning in Predicting Post-Stroke Depression: A Systematic Review and Meta-Analysis.

INTRODUCTION: Post-stroke depression is one of the important complications of stroke and affects pat...

May 2025 40418113

Identifying individuals at risk of post-stroke depression: Development and validation of a predictive model.

OBJECTIVES: To identify the factors associated with post-stroke depression (PSD) and develop a machi...

(1)

May 2025 40335101

Exploratory Analysis of Nationwide Japanese Patient Safety Reports on Suicide and Suicide Attempts Among Inpatients With Cancer Using Large Language Models.

OBJECTIVE: Patients with cancer have a high risk of suicide. However, evidence-based preventive meas...

May 2025 40320591

Frequency Feature Fusion Graph Network For Depression Diagnosis Via fNIRS

Data-driven approaches for depression diagnosis have emerged as a significant research focus in ne...

Apr 2025 http://arxiv.org/abs/2504.21064v1

Deep Learning Characterizes Depression and Suicidal Ideation from Eye Movements

Identifying physiological and behavioral markers for mental health conditions is a longstanding ch...

(1)

Apr 2025 http://arxiv.org/abs/2504.20944v1

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis

Major depressive disorder (MDD) impacts more than 300 million people worldwide, highlighting a sig...

Apr 2025 http://arxiv.org/abs/2505.00032v1

MAGI: Multi-Agent Guided Interview for Psychiatric Assessment

Automating structured clinical interviews could revolutionize mental healthcare accessibility, yet...

(1)

Apr 2025 http://arxiv.org/abs/2504.18260v1

[Construction of recognition models for subthreshold depression based on multiple machine learning algorithms and vocal emotional characteristics].

OBJECTIVES: To construct vocal recognition classification models using 6 machine learning algorithms...

(1)

Apr 2025 40294920

Apr 2025 http://arxiv.org/abs/2504.04739v1

Psychiatry

Browse Categories

Population-Wide Depression Incidence Forecasting Comparing Autoregressive Integrated Moving Average and Vector Autoregressive Integrated Moving Average to Temporal Fusion Transformers: Longitudinal Observational Study.

Reasoning language models for more transparent prediction of suicide risk.

Voice biomarkers of perinatal depression: cross-sectional nationwide pilot study report

Construction and validation of a predictive model for suicidal ideation in non-psychiatric elderly inpatients.

Fair Uncertainty Quantification for Depression Prediction

Predicting peripartum depression using elastic net regression and machine learning: the role of remnant cholesterol.

Identifying most important predictors for suicidal thoughts and behaviours among healthcare workers active during the Spain COVID-19 pandemic: a machine-learning approach.

A Deep Learning approach for Depressive Symptoms assessment in Parkinson's disease patients using facial videos

An Explainable Anomaly Detection Framework for Monitoring Depression and Anxiety Using Consumer Wearable Devices

Accuracy of Machine Learning in Predicting Post-Stroke Depression: A Systematic Review and Meta-Analysis.

Identifying individuals at risk of post-stroke depression: Development and validation of a predictive model.

Exploratory Analysis of Nationwide Japanese Patient Safety Reports on Suicide and Suicide Attempts Among Inpatients With Cancer Using Large Language Models.

Frequency Feature Fusion Graph Network For Depression Diagnosis Via fNIRS

Deep Learning Characterizes Depression and Suicidal Ideation from Eye Movements

MDD-LLM: Towards Accuracy Large Language Models for Major Depressive Disorder Diagnosis

MAGI: Multi-Agent Guided Interview for Psychiatric Assessment

[Construction of recognition models for subthreshold depression based on multiple machine learning algorithms and vocal emotional characteristics].

Wearable-Derived Behavioral and Physiological Biomarkers for Classifying Unipolar and Bipolar Depression Severity

Interpersonal Theory of Suicide as a Lens to Examine Suicidal Ideation in Online Spaces

Leveraging Large Language Models for Cost-Effective, Multilingual Depression Detection and Severity Assessment

MedGNN: Capturing the Links Between Urban Characteristics and Medical Prescriptions

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