Depression

Development and validation of a meta-learner for combining statistical and machine learning prediction models in individuals with depression.

BACKGROUND: The debate of whether machine learning models offer advantages over standard statistical...

Continuous-time probabilistic models for longitudinal electronic health records.

Analysis of longitudinal Electronic Health Record (EHR) data is an important goal for precision medi...

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 ...

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 ident...

Psychosocial Factors and Psychological Characteristics of Personality of Patients with Chronic Diseases Using Artificial Intelligence Data Mining Technology and Wireless Network Cloud Service Platform.

It was to explore the application value of health cloud service platform based on data mining algori...

Large-Scale Textual Datasets and Deep Learning for the Prediction of Depressed Symptoms.

Millions of people worldwide suffer from depression. Assessing, treating, and preventing recurrence ...

Quantifying depression-related language on social media during the COVID-19 pandemic.

INTRODUCTION: The COVID-19 pandemic had clear impacts on mental health. Social media presents an opp...

Polysomnographic identification of anxiety and depression using deep learning.

Anxiety and depression are common psychiatric conditions associated with significant morbidity and h...

Missing data imputation in clinical trials using recurrent neural network facilitated by clustering and oversampling.

In clinical practice, the composition of missing data may be complex, for example, a mixture of miss...

Design and Evaluation of a Postpartum Depression Ontology.

OBJECTIVE: Postpartum depression (PPD) remains an understudied research area despite its high preval...

Quantifying arousal and awareness in altered states of consciousness using interpretable deep learning.

Consciousness can be defined by two components: arousal (wakefulness) and awareness (subjective expe...

Expressions of anger during advising on life dilemmas predict suicide risk among college students.

Research has demonstrated a relationship between anger and suicidality, while real-time authentic em...

Mood State Detection in Handwritten Tasks Using PCA-mFCBF and Automated Machine Learning.

In this research, we analyse data obtained from sensors when a user handwrites or draws on a tablet ...

Automated detection of clinical depression based on convolution neural network model.

As a common mental disorder, depression is placing an increasing burden on families and society. How...

Continuous Scoring of Depression From EEG Signals via a Hybrid of Convolutional Neural Networks.

Depression score is traditionally determined by taking the Beck depression inventory (BDI) test, whi...

Analysis of Clinical Parameters, Drug Consumption and Use of Health Resources in a Southern European Population with Alcohol Abuse Disorder during COVID-19 Pandemic.

The disruption in healthcare attention to people with alcohol dependence, along with psychological d...

Income inequalities, social support and depressive symptoms among older adults in Europe: a multilevel cross-sectional study.

UNLABELLED: This study analysed the association between income inequality and depression from a mult...

Detection of child depression using machine learning methods.

BACKGROUND: Mental health problems, such as depression in children have far-reaching negative effect...

Formulation and physicochemical stability of oil-in-water nanoemulsion loaded with α-terpineol as flavor oil using Quillaja saponins as natural emulsifier.

Alpha-terpineol (α-TOH) is a promising monoterpenoid detaining several biological activities. Howeve...

Understanding Medical Distrust Among African American/Black and Latino Persons Living With HIV With Sub-Optimal Engagement Along the HIV Care Continuum: A Machine Learning Approach.

Medical distrust is a potent barrier to participation in HIV care and medication use among African A...