Psychiatry

Depression

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

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A deep learning framework for automatic diagnosis of unipolar depression.

BACKGROUND AND PURPOSE: In recent years, the development of machine learning (ML) frameworks for aut...

Individualized prediction of depressive disorder in the elderly: A multitask deep learning approach.

INTRODUCTION: Depressive disorder is one of the major public health problems among the elderly. An e...

Machine learning discovery of longitudinal patterns of depression and suicidal ideation.

BACKGROUND AND AIM: Depression is often accompanied by thoughts of self-harm, which are a strong pre...

Clustering suicides: A data-driven, exploratory machine learning approach.

Methods of suicide have received considerable attention in suicide research. The common approach to ...

Combining mobile-health (mHealth) and artificial intelligence (AI) methods to avoid suicide attempts: the Smartcrises study protocol.

BACKGROUND: The screening of digital footprint for clinical purposes relies on the capacity of weara...

Machine-learning-based classification between post-traumatic stress disorder and major depressive disorder using P300 features.

BACKGROUND: The development of optimal classification criteria for specific mental disorders which s...

Symptomatology differences of major depression in psychiatric versus general hospitals: A machine learning approach.

BACKGROUND: Symptomatology differences of major depressive disorder (MDD) in psychiatric and general...

The risks of risk. Regulating the use of machine learning for psychosis prediction.

Recent advances in Machine Learning (ML) have the potential to revolutionise psychosis prediction an...

Can Machine Learning help us in dealing with treatment resistant depression? A review.

BACKGROUND: About one third of patients treated with antidepressant do not show sufficient symptoms ...

Detection of major depressive disorder from linear and nonlinear heart rate variability features during mental task protocol.

BACKGROUND: Major depressive disorder (MDD) is one of the leading causes of disability; however, cur...

Comparison of Magnesium Sulfate and Ketamine with Ropivacaine in Supraclavicular Brachial Plexus Block: A Randomized Controlled Trial.

BACKGROUND: Supraclavicular brachial plexus block offers good operating conditions with limited post...

The utility of artificial intelligence in suicide risk prediction and the management of suicidal behaviors.

OBJECTIVE: Suicide is a growing public health concern with a global prevalence of approximately 800,...

Depression recognition using machine learning methods with different feature generation strategies.

The diagnosis of depression almost exclusively depends on doctor-patient communication and scale ana...

Identifying depression in the National Health and Nutrition Examination Survey data using a deep learning algorithm.

BACKGROUND: As depression is the leading cause of disability worldwide, large-scale surveys have bee...

Spectral signatures of serotonergic psychedelics and glutamatergic dissociatives.

Classic serotonergic psychedelics are remarkable for their capacity to induce reversible alterations...

The Current Research Landscape on the Artificial Intelligence Application in the Management of Depressive Disorders: A Bibliometric Analysis.

Artificial intelligence (AI)-based techniques have been widely applied in depression research and tr...

Machine-learning based brain age estimation in major depression showing no evidence of accelerated aging.

Molecular biological findings indicate that affective disorders are associated with processes akin t...

Using Machine Learning to Identify Suicide Risk: A Classification Tree Approach to Prospectively Identify Adolescent Suicide Attempters.

This study applies classification tree analysis to prospectively identify suicide attempters among a...

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