Depression

Depression detection for twitter users using sentiment analysis in English and Arabic tweets.

Since depression often results in suicidal thoughts and leaves a person severely disabled daily, the...

A bidirectional thermal sensory leaky integrate-and-fire (LIF) neuron model based on bipolar NbO volatile threshold devices with ultra-low operating current.

Brain-like artificial intelligence (AI) will become the main form and important platform in future c...

Wife-Mother Role Conflict at the Critical Child-Rearing Stage: A Machine-Learning Approach to Identify What and How Matters in Maternal Depression Symptoms in China.

Maternal depression (MD) was one of the most prevalent psychiatric problems worldwide. However, it e...

Volumetric Alterations of the Hippocampal Subfields in Major Depressive Disorder with and without Suicidal Ideation.

Major depressive disorder (MDD) is often accompanied with suicidal ideation (SI). Previous studies s...

Ensemble Approach to Combining Episode Prediction Models Using Sequential Circadian Rhythm Sensor Data from Mental Health Patients.

Managing mood disorders poses challenges in counseling and drug treatment, owing to limitations. Cou...

Development of immersive learning framework (ILF) in achieving the goals of higher education: measuring the impact using a pre-post design.

Emerging technological tools like Artificial Intelligence-based Chatbots, digital educational altern...

Integrating street view images and deep learning to explore the association between human perceptions of the built environment and cardiovascular disease in older adults.

Understanding how built environment attributes affect health remains important. While many studies h...

Examining the Impact of Assistive Technology on Psychological Health, Family Education, and Curriculum Research in Japan: Insights from Artificial Intelligence.

This study aims to analyze the effect of psychological health based on artificial intelligence agent...

Robotic transcranial magnetic stimulation in the treatment of depression: a pilot study.

There has been an increasing demand for robotic coil positioning during repetitive transcranial magn...

Depression in South Korean Adolescents Captured by Text and Opinion Mining of Social Big Data.

Depression in adolescence is recognized as an important social and public health issue that interfer...

Identifying depression in the United States veterans using deep learning algorithms, NHANES 2005-2018.

BACKGROUND: Depression is a common mental health problem among veterans, with high mortality. Despit...

Investigating the effectiveness of socially assistive robot on depression and cognitive functions of community dwelling older adults with cognitive impairments.

We evaluated a socially assistive robot (SAR) named Hyodol during a six-week intervention. This stud...

Artificial intelligence-based approaches for suicide prediction: Hope or hype?

Accurate prediction of suicide risk is important because it allows evidence-based interventions to b...

Identification of Child Survivors of Sex Trafficking From Electronic Health Records: An Artificial Intelligence Guided Approach.

Survivors of child sex trafficking (SCST) experience high rates of adverse health outcomes. Amidst t...

Prediction of suicidal ideation in children and adolescents using machine learning and deep learning algorithm: A case study in South Korea where suicide is the leading cause of death.

BACKGROUND: Korea has the highest suicide rate among Organisation for Economic Co-operation and Deve...

Assessment of depression and anxiety in young and old with a question-based computational language approach.

Middle aged adults experience depression and anxiety differently than younger adults. Age may affect...

Privacy-Preserving Federated Model Predicting Bipolar Transition in Patients With Depression: Prediction Model Development Study.

BACKGROUND: Mood disorder has emerged as a serious concern for public health; in particular, bipolar...

Analyzing of optimal classifier selection for EEG signals of depression patients based on intelligent fuzzy decision support systems.

Electroencephalograms (EEG) is used to assess patients' clinical records of depression (EEG). The di...

Leveraging Natural Language Processing to Improve Electronic Health Record Suicide Risk Prediction for Veterans Health Administration Users.

Suicide risk prediction models frequently rely on structured electronic health record (EHR) data, i...

ChatGPT on ECT: Can Large Language Models Support Psychoeducation?

Public Surveillance of Social Media for Suicide Using Advanced Deep Learning Models in Japan: Time Series Study From 2012 to 2022.

BACKGROUND: Social media platforms have been increasingly used to express suicidal thoughts, feeling...