Psychiatry

Depression

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

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Deep learning based classification of facial dermatological disorders.

Common properties of dermatological diseases are mostly lesions with abnormal pattern and skin color...

Interpretation of Depression Detection Models via Feature Selection Methods.

Given the prevalence of depression worldwide and its major impact on society, several studies employ...

Assessing the predictive ability of the Suicide Crisis Inventory for near-term suicidal behavior using machine learning approaches.

OBJECTIVE: This study explores the prediction of near-term suicidal behavior using machine learning ...

Suicide Risk Assessment Using Machine Learning and Social Networks: a Scoping Review.

According to the World Health Organization (WHO) report in 2016, around 800,000 of individuals have ...

Automated Smart Home Assessment to Support Pain Management: Multiple Methods Analysis.

BACKGROUND: Poorly managed pain can lead to substance use disorders, depression, suicide, worsening ...

Classification of Depression Through Resting-State Electroencephalogram as a Novel Practice in Psychiatry: Review.

BACKGROUND: Machine learning applications in health care have increased considerably in the recent p...

Deep learning with wearable based heart rate variability for prediction of mental and general health.

The ubiquity and commoditisation of wearable biosensors (fitness bands) has led to a deluge of perso...

Using Machine Learning to Predict Suicide Attempts in Military Personnel.

Identifying predictors of suicide attempts is critical in intervention and prevention efforts, yet f...

EEG-based deep learning model for the automatic detection of clinical depression.

Clinical depression is a neurological disorder that can be identified by analyzing the Electroenceph...

Learning Individualized Treatment Rules for Multiple-Domain Latent Outcomes.

For many mental disorders, latent mental status from multiple-domain psychological or clinical sympt...

A peripheral inflammatory signature discriminates bipolar from unipolar depression: A machine learning approach.

BACKGROUND: Mood disorders (major depressive disorder, MDD, and bipolar disorder, BD) are considered...

Deep neural networks detect suicide risk from textual facebook posts.

Detection of suicide risk is a highly prioritized, yet complicated task. Five decades of research ha...

Identifying and validating subtypes within major psychiatric disorders based on frontal-posterior functional imbalance via deep learning.

Converging evidence increasingly implicates shared etiologic and pathophysiological characteristics ...

Can machine learning be useful as a screening tool for depression in primary care?

Depression is a widespread disease with a high economic burden and a complex pathophysiology disease...

Multi-dimensional predictions of psychotic symptoms via machine learning.

The diagnostic criteria for schizophrenia comprise a diverse range of heterogeneous symptoms. As a r...

Precision psychiatry in clinical practice.

The treatment of depression represents a major challenge for healthcare systems and choosing among t...

Identifying resting-state effective connectivity abnormalities in drug-naïve major depressive disorder diagnosis via graph convolutional networks.

Major depressive disorder (MDD) is a leading cause of disability; its symptoms interfere with social...

Disrupted rich-club network organization and individualized identification of patients with major depressive disorder.

BACKGROUND: Altered structural and functional brain networks have been extensively studied in major ...

Artificial Intelligence and Suicide Prevention: A Systematic Review of Machine Learning Investigations.

Suicide is a leading cause of death that defies prediction and challenges prevention efforts worldwi...

Construction of gene-classifier and co-expression network analysis of genes in association with major depressive disorder.

Because the pathogenesis of major depressive disorder (MDD) is still unclear and the accurate diagno...

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