Depression

EEG-based Depression Detection Using Convolutional Neural Network with Demographic Attention Mechanism.

Electroencephalography (EEG)-based depression detection has become a hot topic in the development of...

Depression Scale Prediction with Cross-Sample Entropy and Deep Learning.

A two-stage deep learning-based scheme is presented to predict the Hamilton Depression Scale (HAM-D)...

Can machine-learning methods really help predict suicide?

PURPOSE OF REVIEW: In recent years there has been interest in the use of machine learning in suicide...

Antidepressant pathways of the Chinese herb through genetic ontology analysis.

Active compounds and corresponding targets of the traditional Chinese herb, were obtained from syst...

Depression screening using mobile phone usage metadata: a machine learning approach.

OBJECTIVE: Depression is currently the second most significant contributor to non-fatal disease burd...

Natural language processing for structuring clinical text data on depression using UK-CRIS.

BACKGROUND: Utilisation of routinely collected electronic health records from secondary care offers ...

Effects of innovative hip-knee-ankle interlimb coordinated robot training on ambulation, cardiopulmonary function, depression, and fall confidence in acute hemiplegia.

BACKGROUND: While Walkbot-assisted locomotor training (WLT) provided ample evidence on balance and g...

Personalized prognostic prediction of treatment outcome for depressed patients in a naturalistic psychiatric hospital setting: A comparison of machine learning approaches.

OBJECTIVE: Research on predictors of treatment outcome in depression has largely derived from random...

Targeted prescription of cognitive-behavioral therapy versus person-centered counseling for depression using a machine learning approach.

OBJECTIVE: Depression is a highly common mental disorder and a major cause of disability worldwide. ...

Prediction of Sex-Specific Suicide Risk Using Machine Learning and Single-Payer Health Care Registry Data From Denmark.

IMPORTANCE: Suicide is a public health problem, with multiple causes that are poorly understood. The...

Changes in Functional Connectivity Predict Outcome of Repetitive Transcranial Magnetic Stimulation Treatment of Major Depressive Disorder.

Repetitive transcranial magnetic stimulation (rTMS) treatment of major depressive disorder (MDD) is ...

What health records data are required for accurate prediction of suicidal behavior?

OBJECTIVE: The study sought to evaluate how availability of different types of health records data a...

Applying Natural Language Processing to Evaluate News Media Coverage of Bullying and Cyberbullying.

Bullying events have frequently been the focus of coverage by news media, including news stories abo...

Leveraging Digital Health and Machine Learning Toward Reducing Suicide-From Panacea to Practical Tool.

Integration of machine learning and pharmacogenomic biomarkers for predicting response to antidepressant treatment: can computational intelligence be used to augment clinical assessments?

Elucidating Compound Mechanism of Action and Predicting Cytotoxicity Using Machine Learning Approaches, Taking Prediction Confidence into Account.

The modes of action (MoAs) of drugs frequently are unknown, because many are small molecules initial...

Identifying Suicidal Adolescents from Mental Health Records Using Natural Language Processing.

Suicidal ideation is a risk factor for self-harm, completed suicide and can be indicative of mental ...

Text Classification to Inform Suicide Risk Assessment in Electronic Health Records.

Assessing a patient's risk of an impending suicide attempt has been hampered by limited information ...

Evaluation of a Companion Robot for Individuals With Dementia: Quantitative Findings of the MARIO Project in an Irish Residential Care Setting.

The current study focuses on the short-term effect of MARIO, a social robot, on quality of life, dep...

A Social Media Study on the Effects of Psychiatric Medication Use.

Understanding the effects of psychiatric medications during mental health treatment constitutes an a...

RRAM-based synapse devices for neuromorphic systems.

Hardware artificial neural network (ANN) systems with high density synapse array devices can perform...