Psychiatry

Depression

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

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Showing 1219-1239 of 1,937 articles
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...

Oct 2020 33090373
Using Machine Learning to Predict Suicide Attempts in Military Personnel.

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

Oct 2020 33113452
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...

Oct 2020 33045321
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...

Oct 2020 33028921
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 ...

Oct 2020 33005028
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...

Sep 2020 33035759
Multi-dimensional predictions of psychotic symptoms via machine learning.

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

Sep 2020 32870535
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...

Aug 2020 32813309
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 ...

Aug 2020 32818534
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...

Aug 2020 32824149
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...

(2)
Aug 2020 32823199
Caregiver burden in stroke inpatients: a randomized study comparing robot-assisted gait training and conventional therapy.

The effects of caregiver burden during the inpatient rehabilitation period have not yet been investi...

Aug 2020 32776169
Test-Retest Reliability of Kinematic Assessments for Upper Limb Robotic Rehabilitation.

Robot-measured kinematic variables are increasingly used in neurorehabilitation to characterize moto...

Aug 2020 32746329
Major depressive disorder diagnosis based on effective connectivity in EEG signals: a convolutional neural network and long short-term memory approach.

Deep learning techniques have recently made considerable advances in the field of artificial intelli...

Jul 2020 33854642
Speech Quality Feature Analysis for Classification of Depression and Dementia Patients.

Loss of cognitive ability is commonly associated with dementia, a broad category of progressive brai...

Jun 2020 32604728
Major Depressive Disorder Classification Based on Different Convolutional Neural Network Models: Deep Learning Approach.

The human brain is characterized by complex structural, functional connections that integrate unique...

Jun 2020 32491928
Pediatric Acute-Onset Neuropsychiatric Syndrome: A Data Mining Approach to a Very Specific Constellation of Clinical Variables.

Pediatric acute onset neuropsychiatric syndrome (PANS) is a clinically heterogeneous disorder prese...

May 2020 32460516
Detection of Depression and Scaling of Severity Using Six Channel EEG Data.

Depression is a psychiatric problem which affects the growth of a person, like how a person thinks, ...

(2)
May 2020 32435986
Improved metabolomic data-based prediction of depressive symptoms using nonlinear machine learning with feature selection.

To solve major limitations in algorithms for the metabolite-based prediction of psychiatric phenotyp...

(1)
May 2020 32427830
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