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Depression

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

Scientific reports
Electroencephalograms (EEG) is used to assess patients' clinical records of depression (EEG). The disorder of human thinking is a very complex problem caused by heavy-duty in daily life. We need some future and optimal classifier selection by using d...

Pain, dynamic postural control, mental health and impact of oral health in individuals with temporomandibular disorder: A cross-sectional study.

Journal of bodywork and movement therapies
INTRODUCTION: Some studies claim that functional changes in TMD affect the stomatognathic system (SS) and could contribute to the emergence of pain and changes in postural control.

Machine Learning and Electroencephalogram Signal based Diagnosis of Dipression.

Neuroscience letters
Depression is a psychological condition which hampers day to day activity (Thinking, Feeling or Action). The early detection of this illness will help to save many lives because it is now recognized as a global problem which could even lead to suicid...

Higher depression risks in medium- than in high-density urban form across Denmark.

Science advances
Urban areas are associated with higher depression risks than rural areas. However, less is known about how different types of urban environments relate to depression risk. Here, we use satellite imagery and machine learning to quantify three-dimensio...

Development of deep learning model and evaluation in real clinical practice of lingual mandibular bone depression (Stafne cyst) on panoramic radiographs.

Dento maxillo facial radiology
OBJECTIVES: Lingual mandibular bone depression (LMBD) is a developmental bony defect in the lingual aspect of the mandible that does not require any surgical treatment. It is sometimes confused with a cyst or another radiolucent pathologic lesion on ...

Identifying the Influencing Factors of Depressive Symptoms among Nurses in China by Machine Learning: A Multicentre Cross-Sectional Study.

Journal of nursing management
BACKGROUND: Nurses' high workload can result in depressive symptoms. However, the research has underexplored the internal and external variables, such as organisational support, career identity, and burnout, which may predict depressive symptoms amon...

Prevalence of depressive symptoms and associated factors during the COVID-19 pandemic: A national-based study.

Journal of affective disorders
BACKGROUND: Previous studies have reported that the prevalence of depression and depressive symptoms was significantly higher than that before the COVID-19 pandemic. This study aimed to explore the prevalence of depressive symptoms and evaluate the i...

The Association between Artificial Intelligence Awareness and Employee Depression: The Mediating Role of Emotional Exhaustion and the Moderating Role of Perceived Organizational Support.

International journal of environmental research and public health
The combination of artificial intelligence (AI) technology with the real economy has dramatically improved the efficiency of enterprises. However, the replacement of AI for employment also significantly impacts employees' cognition and psychological ...

Uncovering psychiatric phenotypes using unsupervised machine learning: A data-driven symptoms approach.

European psychiatry : the journal of the Association of European Psychiatrists
BACKGROUND: Current categorical classification systems of psychiatric diagnoses lead to heterogeneity of symptoms within disorders and common co-occurrence of disorders. We investigated the heterogeneous and overlapping nature of symptom endorsement ...

Effects of a cognitive-based intervention program using social robot PIO on cognitive function, depression, loneliness, and quality of life of older adults living alone.

Frontiers in public health
OBJECTIVE: Social robot interventions are being implemented to reduce cognitive decline, depression, and loneliness among older adults. However, the types, functions, and programs of effective social robots have not yet been confirmed. This study inv...