AIMC Topic: Depression

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

International journal of environmental research and public health
Audio features are physical features that reflect single or complex coordinated movements in the vocal organs. Hence, in speech-based automatic depression classification, it is critical to consider the relationship among audio features. Here, we prop...

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

Sensors (Basel, Switzerland)
In today's world, mental health diseases have become highly prevalent, and depression is one of the mental health problems that has become widespread. According to WHO reports, depression is the second-leading cause of the global burden of diseases. ...

Socially Assistive Humanoid Robots: Effects on Depression and Health-Related Quality of Life among Low-Income, Socially Isolated Older Adults in South Korea.

Journal of applied gerontology : the official journal of the Southern Gerontological Society
Using a mixed-method study design, we examined the effects of a socially assistive humanoid robot (SAHR), called Hyodol, on depressive symptoms and health-related quality of life (HRQOL) of low-income, socially isolated older adults ( = 180). Quantit...

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

Advanced materials (Deerfield Beach, Fla.)
Neuromorphic engineering and artificial intelligence demands hardware elements that emulates synapse algorithms. During the last decade electrolyte-gated organic conjugated materials have been explored as a platform for artificial synapses for neurom...

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

Medical engineering & physics
Stress, depression, and anxiety are a person's physiological states that emerge from various body features such as speech, body language, eye contact, facial expression, etc. Physiological emotion is a part of human life and is associated with psycho...

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

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
BACKGROUND: In recent years, more and more people suffer from depression and anxiety. These symptoms are hard to be spotted and can be very dangerous. Currently, the Self-Reported Anxiety Scale (SAS) and Self-Reported Depression Scale (SDS) are commo...

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

Computer methods and programs in biomedicine
BACKGROUND: Depression (Major Depressive Disorder) is one of the most common mental illnesses. According to the World Health Organization, more than 300 million people in the world are affected. A first depressive episode can be solved by a spontaneo...

Comparison of three machine learning models to predict suicidal ideation and depression among Chinese adolescents: A cross-sectional study.

Journal of affective disorders
BACKGROUND: Machine learning (ML) algorithms based on various clinicodemographic, psychometric, and biographic factors have been used to predict depression, suicidal ideation, and suicide attempt in adolescents, but there is still a need for more acc...

The Impact of Engagement with the PARO Therapeutic Robot on the Psychological Benefits of Older Adults with Dementia.

Clinical gerontologist
OBJECTIVES: This study aimed to examine the effect of 8-weeks of a 60-minute PARO intervention to reduce depressive symptoms and loneliness in older adults with dementia and investigated changes in their emotional or behavioral expressions and level ...

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

International journal of neural systems
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...