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Depression

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The Current Research Landscape on the Artificial Intelligence Application in the Management of Depressive Disorders: A Bibliometric Analysis.

International journal of environmental research and public health
Artificial intelligence (AI)-based techniques have been widely applied in depression research and treatment. Nonetheless, there is currently no systematic review or bibliometric analysis in the medical literature about the applications of AI in depre...

Early Detection of Depression: Social Network Analysis and Random Forest Techniques.

Journal of medical Internet research
BACKGROUND: Major depressive disorder (MDD) or depression is among the most prevalent psychiatric disorders, affecting more than 300 million people globally. Early detection is critical for rapid intervention, which can potentially reduce the escalat...

Using heart rate profiles during sleep as a biomarker of depression.

BMC psychiatry
BACKGROUND: Abnormalities in heart rate during sleep linked to impaired neuro-cardiac modulation may provide new information about physiological sleep signatures of depression. This study assessed the validity of an algorithm using patterns of heart ...

Artificial Intelligence based facial recognition for Mood Charting among men on life style modification and it's correlation with cortisol.

Asian journal of psychiatry
UNLABELLED: Today, clinicians and researchers believe that mood disorders in children and adolescents remain one of the most under diagnosed mental health problems. Mood disorders in adolescents also put them at risk for other conditions that may per...

Giving Voice to Vulnerable Children: Machine Learning Analysis of Speech Detects Anxiety and Depression in Early Childhood.

IEEE journal of biomedical and health informatics
Childhood anxiety and depression often go undiagnosed. If left untreated these conditions, collectively known as internalizing disorders, are associated with long-term negative outcomes including substance abuse and increased risk for suicide. This p...

Combining heterogeneous data sources for neuroimaging based diagnosis: re-weighting and selecting what is important.

NeuroImage
Combining neuroimaging and clinical information for diagnosis, as for example behavioral tasks and genetics characteristics, is potentially beneficial but presents challenges in terms of finding the best data representation for the different sources ...

EEG-based mild depression recognition using convolutional neural network.

Medical & biological engineering & computing
Electroencephalography (EEG)-based studies focus on depression recognition using data mining methods, while those on mild depression are yet in infancy, especially in effective monitoring and quantitative measure aspects. Aiming at mild depression re...

Predicting inadequate postoperative pain management in depressed patients: A machine learning approach.

PloS one
Widely-prescribed prodrug opioids (e.g., hydrocodone) require conversion by liver enzyme CYP-2D6 to exert their analgesic effects. The most commonly prescribed antidepressant, selective serotonin reuptake inhibitors (SSRIs), inhibits CYP-2D6 activity...

Recent Developments in the Treatment of Depression.

Behavior therapy
The cognitive and behavioral interventions can be as efficacious as antidepressant medications and more enduring, but some patients will be more likely to respond to one than the other. Recent work has focused on developing sophisticated selection al...