Bipolar Disorder

Discriminating between major depressive disorder and bipolar depression: Aberrant EEG microstate dynamics and machine learning classification.

BACKGROUND: Major depressive disorder (MDD) and bipolar depression (BD) are common mood disorders with overlapping clinical features, posing significant challenges for accurate diagnosis and effective treatment. Electroencephalography (EEG) microstates reflect transient, quasi-stable patterns of brain activity that index fast, large-scale neural network dynamics and may provide novel insights into...

Implementing artificial intelligence (AI) to facilitate health outcomes in mood disorders: Application versus aspiration.

The burden of depressive and bipolar disorders at the individual and societal level are extraordinary and increasing. For decades, evidence-based treatments for these conditions have been established but outcomes amongst individuals with lived experience remains suboptimal. Notwithstanding calls to close gaps between current practice and best practice, there is an absence of evidence that overall ...

A machine learning approach to predicting clinical trajectories in bipolar disorder.

BACKGROUND: Bipolar disorder (BD) is characterized by significant heterogeneity in clinical presentation, age of onset, and diagnostic delays. Identif...

Identification and experimental confirmation of TBC1D10C as a shared transcriptional link between abdominal aortic aneurysm and major depressive disorder.

BACKGROUND: Abdominal aortic aneurysm (AAA) and major depressive disorder (MDD) are prevalent conditions with substantial global health burdens. Growi...

Prevalence and factors associated with suicidal ideation based on the Malaysia National Health and Morbidity Survey: A machine learning analysis.

BACKGROUND: This study estimated the prevalence of past-two-week suicidal ideation and examined its demographic, clinical, and health-related correlat...

Association of wearable-sensor derived gait measures with cartilage damage over 2 years in the Multicenter Osteoarthritis Study.

PURPOSE: Gait affects knee loading. Modifying gait could reduce load and protect against cartilage loss. Our objective is to look for modifiable gait ...

Interconnected Cognitive and Neuroimmune Impairments in Schizophrenia: Modulating Effects of Antipsychotic Type, Illness Duration, and Symptom Severity.

OBJECTIVE: Cognitive impairment in schizophrenia (SCZ) is associated with neuroinflammation and neurotrophic dysregulation. The role of pro-inflammato...

Design and predictive modeling of a veterinary drug detection sensor in paddy field water based on artificial neural networks.

For rapid real-time detection of veterinary drug residues in paddy field water, we developed a novel sensor system using interdigitated electrodes as ...

What stole Chinese older adults' life satisfaction? Integrating medical statistics and machine learning with a life-course perspective using CHARLS data.

BACKGROUND: As China enters a rapidly aging era, understanding the determinants of life satisfaction among older adults has become a pressing research...

Accelerated brain aging in prolonged grief disorder of later life: Influence of comorbid depression.

BACKGROUND: Prolonged Grief Disorder (PGD) in later life may involve volumetric patterns indicative of accelerated brain aging. This study examined wh...

Using AI to Train Future Clinicians in Depression Assessment: Feasibility Study.

BACKGROUND: Depression is a major global health care challenge, causing significant individual distress but also contributing to a substantial global ...

Postmarketing Safety of Transcranial Magnetic Stimulation: A 10-Year MAUDE Database Analysis of Adverse Events and Technological Advancements.

Background: Transcranial magnetic stimulation (TMS) is an FDA-cleared neuromodulation technique with expanding clinical applications beyond major depr...

Immune-related biomarkers for major depressive disorder identified via integrated bioinformatics and machine learning.

Background: Major depressive disorder (MDD) is a leading cause of disability worldwide, yet its early and objective diagnosis remains challenging due ...

Multimodal machine learning models for predicting remission in major depressive disorder using clinical data, blood biomarkers, and DNA methylation.

Major depressive disorder (MDD) is a leading global health burden, yet only one-third of patients achieve remission with initial antidepressant therap...

Functional Inputs to the Subgenual Cingulate Cortex Differentiate Levels of Depressive Symptom Severity in Neurotypical Young Adults: Granger Causality and Clustering Analyses.

Extant research has implicated functional connectivity of the subgenual anterior cingulate cortex (sgACC) in major depressive disorders or depressive ...

MS-STFNN: A multi-scale spatio-temporal fusion neural network for fMRI-based depression diagnosis.

Major depressive disorder (MDD) is a common mental disorder. Current clinical diagnosis primarily relies on subjective scales, underscoring an urgent ...

Targeting the MPO/LCN2/GMPPB axis in IBS-depression comorbidity: Integrated multi-omics and bidirectional network pharmacology for precision diagnostics and therapeutics.

BACKGROUND: Irritable Bowel Syndrome (IBS) and Major Depressive Disorder (MDD) exhibit high comorbidity, driven by dysregulation of gut-brain axis int...

Toward personalized classification and treatment in depression: A narrative review of digital phenotyping and artificial intelligence.

Major depressive disorder (MDD) remains a highly heterogeneous condition, presenting significant challenges for effective diagnosis and treatment. Tra...

Changes in Phasic Heart Rate Variability Predict Clinical Outcomes Following Emotion Regulation Therapy for Generalized Anxiety Disorder and Comorbid Depression.

Generalized anxiety disorder (GAD) and major depressive disorder (MDD) frequently co-occur and are marked by greater chronicity, severity, and poorer ...

Machine learning molecular dynamics simulations of coordination and diffusion behaviors in lithiated gallium electrodes.

Liquid gallium (Ga) has emerged as a promising anode material for flexible lithium-ion batteries owing to its exceptional fluidity, intrinsic self-hea...