AIMC Topic: Depression

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

Scientific reports
There has been an increasing demand for robotic coil positioning during repetitive transcranial magnetic stimulation (rTMS) treatment. Accurate coil positioning is crucial because rTMS generally targets specific brain regions for both research and cl...

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

BMC psychiatry
BACKGROUND: Depression is a common mental health problem among veterans, with high mortality. Despite the numerous conducted investigations, the prediction and identification of risk factors for depression are still severely limited. This study used ...

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

Assistive technology : the official journal of RESNA
We evaluated a socially assistive robot (SAR) named Hyodol during a six-week intervention. This study enrolled 69 older adults with cognitive decline. To screen the eligibility, we have used the following three criteria, namely Korean-Mini-Mental Sta...

Identifying multilevel predictors of trajectories of psychopathology and resilience among juvenile offenders: A machine learning approach.

Development and psychopathology
Mental ill health is more common among juvenile offenders relative to adolescents in general. Little is known about individual differences in their long-term psychological adaptation and its predictors from multiple aspects of their life. This study ...

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

Journal of medical Internet research
BACKGROUND: Mood disorder has emerged as a serious concern for public health; in particular, bipolar disorder has a less favorable prognosis than depression. Although prompt recognition of depression conversion to bipolar disorder is needed, early pr...

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...