Psychiatry

Depression

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

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Using Natural Language Processing to develop risk-tier specific suicide prediction models for Veterans Affairs patients.

Suicide is a leading cause of death. Suicide rates are particularly elevated among Department of Vet...

Future of service member monitoring: the intersection of biology, wearables and artificial intelligence.

While substantial investment has been made in the early identification of mental and behavioural hea...

Application Value of a Machine Learning Model in Predicting Mild Depression Associated with Migraine without Aura.

To investigate the application value of a machine learning model in predicting mild depression asso...

Using deep learning and pretreatment EEG to predict response to sertraline, bupropion, and placebo.

OBJECTIVE: Predicting an individual's response to antidepressant medication remains one of the most ...

Machine learning-based discrimination of unipolar depression and bipolar disorder with streamlined shortlist in adolescents of different ages.

BACKGROUND: Variations in symptoms and indistinguishable depression episodes of unipolar depression ...

Temporal dynamic alterations of regional homogeneity in major depressive disorder: a study integrating machine learning.

Previous studies have found alterations in the local regional homogeneity of brain activity in indiv...

Global Suicide Mortality Rates (2000-2019): Clustering, Themes, and Causes Analyzed through Machine Learning and Bibliographic Data.

Suicide research is directed at understanding social, economic, and biological causes of suicide tho...

Deep Learning-Based Artificial Intelligence Can Differentiate Treatment-Resistant and Responsive Depression Cases with High Accuracy.

Although there are many treatment options available for depression, a large portion of patients wit...

Suicidal behaviors among high school graduates with preexisting mental health problems: A machine learning and GIS-based study.

BACKGROUND: Suicidal behavior among adolescents with mental health disorders, such as depression and...

Risk factors for depression in China based on machine learning algorithms: A cross-sectional survey of 264,557 non-manual workers.

BACKGROUND: Factors related to depression differ depending on the population studied, and studies fo...

Prediction of anhedonia in patients with first-episode schizophrenia using a Wavelet-ALFF-based Support vector regression model.

Anhedonia is one of the core features of the negative symptoms of schizophrenia and can be extremely...

HEMAsNet: A Hemisphere Asymmetry Network Inspired by the Brain for Depression Recognition From Electroencephalogram Signals.

Depression is a prevalent mental disorder that affects a significant portion of the global populatio...

EEGDepressionNet: A Novel Self Attention-Based Gated DenseNet With Hybrid Heuristic Adopted Mental Depression Detection Model Using EEG Signals.

World Health Organization (WHO) has identified depression as a significant contributor to global dis...

Natural Language Processing for Depression Prediction on Sina Weibo: Method Study and Analysis.

BACKGROUND: Depression represents a pressing global public health concern, impacting the physical an...

Machine Learning Model Reveals Determinators for Admission to Acute Mental Health Wards From Emergency Department Presentations.

This research addresses the critical issue of identifying factors contributing to admissions to acut...

DepressionEmo: A novel dataset for multilabel classification of depression emotions.

Emotions are integral to human social interactions, with diverse responses elicited by various situa...

Identification of Pyroptosis-Related Molecular Subtypes and Diagnostic Model development in Major Depressive Disorder.

Major depressive disorder (MDD) is a prevalent psychological disorder associated with inflammation, ...

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