Psychiatry

Depression

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

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Early Detection of Depression: Social Network Analysis and Random Forest Techniques.

BACKGROUND: Major depressive disorder (MDD) or depression is among the most prevalent psychiatric di...

Using heart rate profiles during sleep as a biomarker of depression.

BACKGROUND: Abnormalities in heart rate during sleep linked to impaired neuro-cardiac modulation may...

Prediction models for high risk of suicide in Korean adolescents using machine learning techniques.

OBJECTIVE: Suicide in adolescents is a major problem worldwide and previous history of suicide ideat...

Prediction of rTMS treatment response in major depressive disorder using machine learning techniques and nonlinear features of EEG signal.

BACKGROUND: Prediction of therapeutic outcome of repetitive transcranial magnetic stimulation (rTMS)...

Diagnosis of Human Psychological Disorders using Supervised Learning and Nature-Inspired Computing Techniques: A Meta-Analysis.

A psychological disorder is a mutilation state of the body that intervenes the imperative functionin...

Deep Sequential Models for Suicidal Ideation From Multiple Source Data.

This paper presents a novel method for predicting suicidal ideation from electronic health records (...

See your mental state from your walk: Recognizing anxiety and depression through Kinect-recorded gait data.

As the challenge of mental health problems such as anxiety and depression increasing today, more con...

Detecting depression using a framework combining deep multimodal neural networks with a purpose-built automated evaluation.

Machine learning (ML) has been introduced into the medical field as a means to provide diagnostic to...

Giving Voice to Vulnerable Children: Machine Learning Analysis of Speech Detects Anxiety and Depression in Early Childhood.

Childhood anxiety and depression often go undiagnosed. If left untreated these conditions, collectiv...

Spiking Neural Network Modelling Approach Reveals How Mindfulness Training Rewires the Brain.

There has been substantial interest in Mindfulness Training (MT) to understand how it can benefit he...

Relative importance of symptoms, cognition, and other multilevel variables for psychiatric disease classifications by machine learning.

This study used machine-learning algorithms to make unbiased estimates of the relative importance of...

Evaluating the evidence for biotypes of depression: Methodological replication and extension of.

BACKGROUND: Psychiatric disorders are highly heterogeneous, defined based on symptoms with little co...

Classifying major depression patients and healthy controls using EEG, eye tracking and galvanic skin response data.

OBJECTIVE: Major depression disorder (MDD) is one of the most prevalent mental disorders worldwide. ...

Artificial intelligence based discovery of the association between depression and chronic fatigue syndrome.

BACKGROUND: Both of the modern medicine and the traditional Chinese medicine classify depressive dis...

EEG-based mild depression recognition using convolutional neural network.

Electroencephalography (EEG)-based studies focus on depression recognition using data mining methods...

Low-rank network signatures in the triple network separate schizophrenia and major depressive disorder.

Brain imaging studies have revealed that functional and structural brain connectivity in the so-call...

A randomized controlled trial of suicide prevention training for primary care providers: a study protocol.

BACKGROUND: Suicide is a national public health crisis and a critical patient safety issue. It is th...

Electroconvulsive Therapy Induces Cortical Morphological Alterations in Major Depressive Disorder Revealed with Surface-Based Morphometry Analysis.

Although electroconvulsive therapy (ECT) is one of the most effective treatments for major depressiv...

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