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Depression

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EEG-based Depression Detection Using Convolutional Neural Network with Demographic Attention Mechanism.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Electroencephalography (EEG)-based depression detection has become a hot topic in the development of biomedical engineering. However, the complexity and nonstationarity of EEG signals are two biggest obstacles to this application. In addition, the ge...

Depression Scale Prediction with Cross-Sample Entropy and Deep Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
A two-stage deep learning-based scheme is presented to predict the Hamilton Depression Scale (HAM-D) in this study. First, the cross-sample entropy (CSE) that allows assessing the degree of similarity of two data series are evaluated for the 90 brain...

Depression screening using mobile phone usage metadata: a machine learning approach.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Depression is currently the second most significant contributor to non-fatal disease burdens globally. While it is treatable, depression remains undiagnosed in many cases. As mobile phones have now become an integral part of daily life, th...

Neuropsychiatric symptoms as predictors of conversion from MCI to dementia: a machine learning approach.

International psychogeriatrics
OBJECTIVES: To use a Machine Learning (ML) approach to compare Neuropsychiatric Symptoms (NPS) in participants of a longitudinal study who developed dementia and those who did not.

Natural language processing for structuring clinical text data on depression using UK-CRIS.

Evidence-based mental health
BACKGROUND: Utilisation of routinely collected electronic health records from secondary care offers unprecedented possibilities for medical science research but can also present difficulties. One key issue is that medical information is presented as ...

Effects of innovative hip-knee-ankle interlimb coordinated robot training on ambulation, cardiopulmonary function, depression, and fall confidence in acute hemiplegia.

NeuroRehabilitation
BACKGROUND: While Walkbot-assisted locomotor training (WLT) provided ample evidence on balance and gait improvements, the therapeutic effects on cardiopulmonary and psychological elements as well as fall confidence are unknown in stroke survivors.

Understanding Mood Disorders in Children.

Advances in experimental medicine and biology
Mood disorders include all types of depression and bipolar disorder, and mood disorders are sometimes called affective disorders. We will discuss newly developing two issues in affective disorders in children and adolescents. Those are the new diagno...

[Artificial Intelligence in Psychiatry].

Brain and nerve = Shinkei kenkyu no shinpo
Diagnosis of psychiatric disorders is based primarily on subjective symptoms, and neuroimaging or other biological examinations are used for excluding organic disorders. Advances in artificial intelligence technologies, such as machine learning, may ...

Predictive markers of depression in hypertension.

Medicine
Hypertension and depression, as 2 major public health issues, are closely related. For patients having hypertension, in particular, depression is a risk factor for mortality and jeopardizes their wellbeing. The aim of the study is to apply support ve...

Depression Severity Classification from Speech Emotion.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Major Depressive Disorder (MDD) is a common psychiatric illness. Automatically classifying depression severity using audio analysis can help clinical management decisions during Deep Brain Stimulation (DBS) treatment of MDD patients. Leveraging the l...