Psychiatry

Bipolar Disorder

Latest AI and machine learning research in bipolar disorder for healthcare professionals.

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Big Data Challenges Targeting Proteins in GPCR Signaling Pathways; Combining PTML-ChEMBL Models and [S]GTPγS Binding Assays.

G-protein-coupled receptors (GPCRs), also known as 7-transmembrane receptors, are the single largest...

Resting-State Functional Network Scale Effects and Statistical Significance-Based Feature Selection in Machine Learning Classification.

In recent years, functional brain network topological features have been widely used as classificati...

Machine Learning Identifies Large-Scale Reward-Related Activity Modulated by Dopaminergic Enhancement in Major Depression.

BACKGROUND: Theoretical models have emphasized systems-level abnormalities in major depressive disor...

Individualized prediction of depressive disorder in the elderly: A multitask deep learning approach.

INTRODUCTION: Depressive disorder is one of the major public health problems among the elderly. An e...

Machine-learning-based classification between post-traumatic stress disorder and major depressive disorder using P300 features.

BACKGROUND: The development of optimal classification criteria for specific mental disorders which s...

Symptomatology differences of major depression in psychiatric versus general hospitals: A machine learning approach.

BACKGROUND: Symptomatology differences of major depressive disorder (MDD) in psychiatric and general...

Can Machine Learning help us in dealing with treatment resistant depression? A review.

BACKGROUND: About one third of patients treated with antidepressant do not show sufficient symptoms ...

Detection of major depressive disorder from linear and nonlinear heart rate variability features during mental task protocol.

BACKGROUND: Major depressive disorder (MDD) is one of the leading causes of disability; however, cur...

A difference degree test for comparing brain networks.

Recently, there has been a proliferation of methods investigating functional connectivity as a bioma...

Decomposition feature selection with applications in detecting correlated biomarkers of bipolar disorders.

Feature selection is an important initial step of exploratory analysis in biomedical studies. Its ma...

Identifying incident dementia by applying machine learning to a very large administrative claims dataset.

Alzheimer's disease and related dementias (ADRD) are highly prevalent conditions, and prior efforts ...

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

Artificial intelligence (AI)-based techniques have been widely applied in depression research and tr...

Machine-learning based brain age estimation in major depression showing no evidence of accelerated aging.

Molecular biological findings indicate that affective disorders are associated with processes akin t...

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

BACKGROUND: Major depressive disorder (MDD) or depression is among the most prevalent psychiatric di...

SynGO: An Evidence-Based, Expert-Curated Knowledge Base for the Synapse.

Synapses are fundamental information-processing units of the brain, and synaptic dysregulation is ce...

Prediction of rTMS treatment response in major depressive disorder using machine learning techniques and nonlinear features of EEG signal.

BACKGROUND: Prediction of therapeutic outcome of repetitive transcranial magnetic stimulation (rTMS)...

Diagnosis of Human Psychological Disorders using Supervised Learning and Nature-Inspired Computing Techniques: A Meta-Analysis.

A psychological disorder is a mutilation state of the body that intervenes the imperative functionin...

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