Depression

Predicting Antidepressant Treatment Response From Cortical Structure on MRI: A Mega-Analysis From the ENIGMA-MDD Working Group.

Accurately predicting individual antidepressant treatment response could expedite the lengthy trial-...

Investigating the Differential Impact of Psychosocial Factors by Patient Characteristics and Demographics on Veteran Suicide Risk Through Machine Learning Extraction of Cross-Modal Interactions.

Accurate prediction of suicide risk is crucial for identifying patients with elevated risk burden, h...

Comparison of six natural language processing approaches to assessing firearm access in Veterans Health Administration electronic health records.

OBJECTIVE: Access to firearms is associated with increased suicide risk. Our aim was to develop a na...

Detection of suicidality from medical text using privacy-preserving large language models.

BACKGROUND: Attempts to use artificial intelligence (AI) in psychiatric disorders show moderate succ...

Predicting Suicides Among US Army Soldiers After Leaving Active Service.

IMPORTANCE: The suicide rate of military servicemembers increases sharply after returning to civilia...

Toward molecular diagnosis of major depressive disorder by plasma peptides using a deep learning approach.

Major depressive disorder (MDD) is a severe psychiatric disorder that currently lacks any objective ...

Analysis of In-Home Movement Patterns for Depression Assessment in Older Adults - A Feasibility Study.

Depression significantly impacts the wellbeing of older Australians, posing considerable challenges ...

Artificial Intelligence in Military Medicine.

Artificial intelligence (AI) has garnered significant attention for its pivotal role in the national...

Machine learning for detection of heterogeneous effects of Medicaid coverage on depression.

In 2008, Oregon expanded its Medicaid program using a lottery, creating a rare opportunity to study ...

A Sentiment Pre-trained Text-Guided Multimodal Cross-Attention Transformer for Improved Depression Detection.

Depression is a widespread mental health issue requiring efficient automated detection methods. Trad...

Diagnosing Suicidal Ideation from Resting State EEG Data Using a Machine Learning Algorithm.

Suicide poses a global health crisis with significant social and economic impact. Prevention may be ...

Exploring Self-Supervised Models for Depressive Disorder Detection: A Study on Speech Corpora.

Automatic detection of depressive disorder from speech signals can help improve medical diagnosis re...

TAU-DI Net: A Multi-Scale Convolutional Network Combining Prob-Sparse Attention for EEG-based Depression Identification.

EEG-based detection of major depression disorder (MDD) plays a pivotal role in the subsequent treatm...

Data Quality Matters: Suicide Intention Detection on Social Media Posts Using RoBERTa-CNN.

Suicide remains a pressing global health concern, necessitating innovative approaches for early dete...

Neural substrates of predicting anhedonia symptoms in major depressive disorder via connectome-based modeling.

MAIN PROBLEM: Anhedonia is a critical diagnostic symptom of major depressive disorder (MDD), being a...

MDDBranchNet: A Deep Learning Model for Detecting Major Depressive Disorder Using ECG Signal.

Major depressive disorder (MDD) is a chronic mental illness which affects people's well-being and is...

Preparing for the bedside-optimizing a postpartum depression risk prediction model for clinical implementation in a health system.

OBJECTIVE: We developed and externally validated a machine-learning model to predict postpartum depr...

[A research on depression recognition based on voice pre-training model].

For the increasing number of patients with depression, this paper proposes an artificial intelligenc...

Machine Learning Algorithms Failed to Find Depression Biomarker.

Geriatric depression and anxiety screening via deep learning using activity tracking and sleep data.

BACKGROUND: Geriatric depression and anxiety have been identified as mood disorders commonly associa...

Artificial Intelligence: A Game-Changer for Mental Health Care.

Starting from the escalating global burden of mental health disorders, exacerbated by the COVID-19 p...