Depression

Adolescent Depression Detection Model Based on Multimodal Data of Interview Audio and Text.

Depression is a common mental disease that has a tendency to develop at a younger age. Early detection of depression with psychological intervention may effectively prevent youth suicide. The establishment of the computer-aided model may be efficient for early detection. However, the existing methods of automatic detection for depression mostly rely on unimodal data. Clinical research shows that p...

Comparisons of deep learning and machine learning while using text mining methods to identify suicide attempts of patients with mood disorders.

BACKGROUND: Suicide attempt is one of the most severe consequences for patients with mood disorders. This study aimed to perform deep learning and machine learning while using text mining to identify patients with suicide attempts and to compare their effectiveness.

Controlled Growth of Wafer-Scale Transition Metal Dichalcogenides with a Vertical Composition Gradient for Artificial Synapses with High Linearity.

Artificial synapses are promising for dealing with large amounts of data computing. Great progress has been made recently in terms of improving the on...

Language-agnostic deep learning framework for automatic monitoring of population-level mental health from social networks.

In many countries, mental health issues are among the most serious public health concerns. National mental health statistics are frequently collected ...

Sex differences in rTMS treatment response: A deep learning-based EEG investigation.

INTRODUCTION: The present study aimed to investigate sex differences in response to repetitive transcranial magnetic stimulation (rTMS) in Major Depre...

Online music-assisted rehabilitation system for depressed people based on deep learning.

The processing of negative emotions is closely related to the occurrence of depression, and improving the mood of patients with depression has an impo...

Automatic Identification of Depression Using Facial Images with Deep Convolutional Neural Network.

BACKGROUND Depression is a common disease worldwide, with about 280 million people having depression. The unique facial features of depression provide...

EEG based depression recognition using improved graph convolutional neural network.

Depression is a global psychological disease that does serious harm to people. Traditional diagnostic method of the doctor-patient communication, is n...

DAC Stacking: A Deep Learning Ensemble to Classify Anxiety, Depression, and Their Comorbidity From Reddit Texts.

Depression is the most incapacitating disease worldwide, and it has an alarming comorbidity rate with anxiety. The use of social networks to expose pe...

Deep learning-based integration of genetics with registry data for stratification of schizophrenia and depression.

Currently, psychiatric diagnoses are, in contrast to most other medical fields, based on subjective symptoms and observable signs and call for new and...

A Machine Learning Approach for Predicting Non-Suicidal Self-Injury in Young Adults.

Artificial intelligence techniques were explored to assess the ability to anticipate self-harming behaviour in the mental health context using a datab...

A novel machine learning approach to shorten depression risk assessment for convenient uses.

BACKGROUND: Depression is a mental disorder affecting many people worldwide which has been exacerbated by the current pandemic. There is an urgent nee...

Perception Exploration on Robustness Syndromes With Pre-processing Entities Using Machine Learning Algorithm.

The majority of the current-generation individuals all around the world are dealing with a variety of health-related issues. The most common cause of ...

The Design of Psychological Education Intervention System in Universities Based on Deep Learning.

With the rapid development of Chinese society and economy as well as the deepening of the reform of the higher education management system and the cha...

Arabic Speech Analysis for Classification and Prediction of Mental Illness due to Depression Using Deep Learning.

Depression is a global prevalent ailment for possible mental illness or mental disorder globally. Recognizing depressed early signs is critical for ev...

Optimized convolution neural network based multiple eye disease detection.

World health organization (WHO) reports around 2.2 billion people in the world as visually challenged which is mostly due to the age-related eye disea...

Continuous-time probabilistic models for longitudinal electronic health records.

Analysis of longitudinal Electronic Health Record (EHR) data is an important goal for precision medicine. Difficulty in applying Machine Learning (ML)...

Suicide Risk Prediction in Clinical Settings-Additional Considerations for Face-to-Face Screening and Machine Learning Approaches.

Depression screening using a non-verbal self-association task: A machine-learning based pilot study.

BACKGROUND: Effective screening is important to combat the raising burden of depression and opens a critical time window for early intervention. Clini...

Employing biochemical biomarkers for building decision tree models to predict bipolar disorder from major depressive disorder.

BACKGROUND: Conventional biochemical parameters may have predictive values for use in clinical identification between bipolar disorder (BD) and major ...