Psychiatry

Depression

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

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Clinician Suicide Risk Assessment for Prediction of Suicide Attempt in a Large Health Care System.

IMPORTANCE: Clinical practice guidelines recommend suicide risk screening and assessment across beha...

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

Computational approaches to predicting mental health conditions in social media have been substantia...

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

Granger causality (GC) effective connectivity (EC) calculated from electroencephalogram (EEG) signal...

Comparative Efficacy of MultiModal AI Methods in Screening for Major Depressive Disorder: Machine Learning Model Development Predictive Pilot Study.

BACKGROUND: Conventional approaches for major depressive disorder (MDD) screening rely on two effect...

Predicting Placebo Responses Using EEG and Deep Convolutional Neural Networks: Correlations with Clinical Data Across Three Independent Datasets.

Identifying likely placebo responders can help design more efficient clinical trials by stratifying ...

Activation of the Carotid Body by Kappa Opioid Receptors Mitigates Fentanyl-Induced Respiratory Depression.

Previous studies reported that opioids depress breathing by inhibiting respiratory neural networks i...

Machine Learning-Based Clinical Decision Support System for Suicide Risk Management: The PERMANENS Project.

The PERMANENS European project addresses the global public health challenge of self-harm and suicide...

COMPASS: Computational mapping of patient-therapist alliance strategies with language modeling.

The therapeutic working alliance is a critical predictor of psychotherapy success. Traditionally, wo...

A machine-learning-derived online prediction model for depression risk in COPD patients: A retrospective cohort study from CHARLS.

BACKGROUND: Depression associated with Chronic Obstructive Pulmonary Disease (COPD) is a detrimental...

Automated Risk Prediction of Post-Stroke Adverse Mental Outcomes Using Deep Learning Methods and Sequential Data.

Depression and anxiety are common comorbidities of stroke. Research has shown that about 30% of stro...

Leveraging neighborhood-level Information to Improve Model Fairness in Predicting Prenatal Depression.

IMPORTANCE: Perinatal depression (PND) affects 10-20% of pregnant women, with significant racial dis...

Major depressive disorder recognition based on electronic handwriting recorded in psychological tasks.

BACKGROUND: This study aimed to determine whether handwriting patterns are altered in individuals ex...

Early detection of mental health disorders using machine learning models using behavioral and voice data analysis.

People of all demographics are impacted by mental illness, which has become a widespread and interna...

Reasoning language models for more transparent prediction of suicide risk.

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

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...

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), ...

EEG-based Signatures of Schizophrenia, Depression, and Aberrant Aging: A Supervised Machine Learning Investigation.

BACKGROUND: Electroencephalography (EEG) is a noninvasive, cost-effective, and robust tool, which di...

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