Psychiatry

Depression

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

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Predictors of suicide ideation among South Korean adolescents: A machine learning approach.

BACKGROUND: The current study developed a predictive model for suicide ideation among South Korean (...

Identifying suicide attempts, ideation, and non-ideation in major depressive disorder from structural MRI data using deep learning.

The present study aims to identify suicide risks in major depressive disorders (MDD) patients from s...

User Feedback on the Use of a Natural Language Processing Application to Screen for Suicide Risk in the Emergency Department.

Suicide is the 10th leading cause of death in the USA and globally. Despite decades of research, the...

Cognitive Depression Detection Cyber-Medical System Based on EEG Analysis and Deep Learning Approaches.

Long-term depression and negative emotional cycles affect life quality and work productivity. Howeve...

Understanding and detecting behaviours prior to a suicide attempt: A mixed-methods study.

OBJECTIVE: Prior research suggests there are observable behaviours preceding suicide attempts in pub...

PRA-Net: Part-and-Relation Attention Network for depression recognition from facial expression.

Artificial intelligence methods are widely applied to depression recognition and provide an objectiv...

Effect of robot-assisted gait training on quality of life and depression in neurological impairment: A systematic review and meta-analysis.

OBJECTIVE: Robot-assisted gait training (RAGT) is often used as a rehabilitation tool for neurologic...

Wearable Artificial Intelligence for Anxiety and Depression: Scoping Review.

BACKGROUND: Anxiety and depression are the most common mental disorders worldwide. Owing to the lack...

Classification of Depression and Its Severity Based on Multiple Audio Features Using a Graphical Convolutional Neural Network.

Audio features are physical features that reflect single or complex coordinated movements in the voc...

Application of Natural Language Processing (NLP) in Detecting and Preventing Suicide Ideation: A Systematic Review.

(1) Introduction: Around a million people are reported to die by suicide every year, and due to the ...

Depression Detection Based on Hybrid Deep Learning SSCL Framework Using Self-Attention Mechanism: An Application to Social Networking Data.

In today's world, mental health diseases have become highly prevalent, and depression is one of the ...

Prediction of monthly dry days with machine learning algorithms: a case study in Northern Bangladesh.

Dry days at varied scale are an important topic in climate discussions. Prolonged dry days define a ...

Key factors selection on adolescents with non-suicidal self-injury: A support vector machine based approach.

Comparing a family structure to a company, one can often think of parents as leaders and adolescents...

An Electrochemical-Electret Coupled Organic Synapse with Single-Polarity Driven Reversible Facilitation-to-Depression Switching.

Neuromorphic engineering and artificial intelligence demands hardware elements that emulates synapse...

Computer assisted identification of stress, anxiety, depression (SAD) in students: A state-of-the-art review.

Stress, depression, and anxiety are a person's physiological states that emerge from various body fe...

Multimodal fusion diagnosis of depression and anxiety based on CNN-LSTM model.

BACKGROUND: In recent years, more and more people suffer from depression and anxiety. These symptoms...

Detecting and Analyzing Suicidal Ideation on Social Media Using Deep Learning and Machine Learning Models.

Individuals who suffer from suicidal ideation frequently express their views and ideas on social med...

A Model of Normality Inspired Deep Learning Framework for Depression Relapse Prediction Using Audiovisual Data.

BACKGROUND: Depression (Major Depressive Disorder) is one of the most common mental illnesses. Accor...

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