Psychiatry

Bipolar Disorder

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

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Showing 211-231 of 830 articles
Immune-based Machine learning Prediction of Diagnosis and Illness State in Schizophrenia and Bipolar Disorder.

BACKGROUND: Schizophrenia and bipolar disorder frequently face significant delay in diagnosis, leadi...

Enhancing Major Depressive Disorder Diagnosis With Dynamic-Static Fusion Graph Neural Networks.

Major Depressive Disorder (MDD) is a debilitating, complex mental condition with unclear mechanisms ...

A Novel Unsupervised Machine Learning Approach to Assess Postural Dynamics in Euthymic Bipolar Disorder.

Bipolar disorder (BD) is a mood disorder with different phases alternating between euthymia, manic o...

Unlocking treatment success: predicting atypical antipsychotic continuation in youth with mania.

PURPOSE: This study aimed to create and validate robust machine-learning-based prediction models for...

Artificial intelligence in the detection and treatment of depressive disorders: a narrative review of literature.

Modern psychiatry aims to adopt precision models and promote personalized treatment within mental he...

Causes of death in individuals with lifetime major depression: a comprehensive machine learning analysis from a community-based autopsy center.

BACKGROUND: Depression can be associated with increased mortality and morbidity, but no studies have...

Detecting depression severity using weighted random forest and oxidative stress biomarkers.

This study employs machine learning to detect the severity of major depressive disorder (MDD) throug...

Role of different omics data in the diagnosis of schizophrenia disorder: A machine learning study.

Schizophrenia is a serious mental disorder that affects millions of people worldwide. This disorder ...

Neuroimaging and natural language processing-based classification of suicidal thoughts in major depressive disorder.

Suicide is a growing public health problem around the world. The most important risk factor for suic...

A deep-learning-based threshold-free method for automated analysis of rodent behavior in the forced swim test and tail suspension test.

BACKGROUND: The forced swim test (FST) and tail suspension test (TST) are widely used to assess depr...

On new common fixed point theorems via bipolar fuzzy -metric space with their applications.

This research work is devoted to investigating new common fixed point theorems on bipolar fuzzy -met...

Machine learning for antidepressant treatment selection in depression.

Finding the right antidepressant for the individual patient with major depressive disorder can be a ...

Glycocalyx shedding patterns identifies antipsychotic-naïve patients with first-episode psychosis.

Psychotic disorders have been linked to immune-system abnormalities, increased inflammatory markers,...

Development of a differential treatment selection model for depression on consolidated and transformed clinical trial datasets.

Major depressive disorder (MDD) is the leading cause of disability worldwide, yet treatment selectio...

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