Psychiatry

Bipolar Disorder

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

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Showing 148-168 of 830 articles
Machine Learning Tool for New Selective Serotonin and Serotonin-Norepinephrine Reuptake Inhibitors.

Depression, a serious mood disorder, affects about 5% of the population. Currently, there are two gr...

Optimal selection of diagnostic method for diabetes mellitus using complex bipolar fuzzy dynamic data.

Diabetes mellitus refers to a collection of metabolic disorders that affect the way carbohydrates ar...

Machine learning for the diagnosis accuracy of bipolar disorder: a systematic review and meta-analysis.

BACKGROUND: Diagnosing bipolar disorder poses a challenge in clinical practice and demands a substan...

The integrating of environmental sustainability assessment by using bipolar complex fuzzy soft Aczel-Alsina aggregation operators with EDAS approach.

The act of responsibly engaging with the world is referred to as environmental sustainability. It en...

Identification of depressive symptoms in adolescents using machine learning combining childhood and adolescence features.

BACKGROUND: Depressive symptoms in adolescents can significantly affect their daily lives and pose r...

Machine learning-based assessment of morphometric abnormalities distinguishes bipolar disorder and major depressive disorder.

INTRODUCTION: Bipolar disorder (BD) and major depressive disorder (MDD) have overlapping clinical pr...

Machine learning-based prediction of illness course in major depression: The relevance of risk factors.

BACKGROUND: Major depressive disorder (MDD) comes along with an increased risk of recurrence and poo...

Natural language processing to identify suicidal ideation and anhedonia in major depressive disorder.

BACKGROUND: Anhedonia and suicidal ideation are symptoms of major depressive disorder (MDD) that are...

Opportunities and Challenges for Clinical Practice in Detecting Depression Using EEG and Machine Learning.

Major depressive disorder (MDD) is associated with substantial morbidity and mortality, yet its diag...

Is Artificial Intelligence the Next Co-Pilot for Primary Care in Diagnosing and Recommending Treatments for Depression?

Depression poses significant challenges to global healthcare systems and impacts the quality of life...

Application of functional near-infrared spectroscopy and machine learning to predict treatment response after six months in major depressive disorder.

Depression treatment responses vary widely among individuals. Identifying objective biomarkers with ...

Enhancing prediction of major depressive disorder onset in adolescents: A machine learning approach.

Major Depressive Disorder (MDD) is a prevalent mental health condition that often begins in adolesce...

Applied pharmacogenetics to predict response to treatment of first psychotic episode: study protocol.

The application of personalized medicine in patients with first-episode psychosis (FEP) requires too...

DDEvENet: Evidence-based ensemble learning for uncertainty-aware brain parcellation using diffusion MRI.

In this study, we developed an Evidential Ensemble Neural Network based on Deep learning and Diffusi...

AI-driven identification of a novel malate structure from recycled lithium-ion batteries.

The integration of Artificial Intelligence (AI) into the discovery of new materials offers significa...

Machine learning prediction model of the treatment response in schizophrenia reveals the importance of metabolic and subjective characteristics.

Predicting early treatment response in schizophrenia is pivotal for selecting the best therapeutic a...

LSTM-based estimation of lithium-ion battery SOH using data characteristics and spatio-temporal attention.

As the primary power source for electric vehicles, the accurate estimation of the State of Health (S...

Diagnosis of major depressive disorder using a novel interpretable GCN model based on resting state fMRI.

The diagnosis and analysis of major depressive disorder (MDD) faces some intractable challenges such...

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