Bipolar Disorder

Prediction of the low-temperature properties of electrolyte solvents for lithium-ion batteries via machine learning.

Electrolytes with low melting points (MPs), high boiling points (BPs), and high dielectric constants (ε) can effectively mitigate performance degradation in lithium-ion batteries (LIBs) under low-temperature conditions. However, the lack of systematic experimental data on electrolyte properties poses a significant challenge to traditional design approaches. To address this limitation, we developed...

Post-secondary student adoption of mental health labels through their use of social media: a scoping review.

BACKGROUND: Social media is a significant source of information for post-secondary students, who are usually at the age at which many common mental disorders first express themselves. Social media can have a role in the way post-secondary students identify and act on mental health issues. OBJECTIVES: Explore how the use of social media influences post-secondary students' adoption of mental health ...

Deep neural network-based analysis of voice biomarkers for monitoring treatment response in adolescent major depressive disorder.

BACKGROUND: In adolescents, identifying objective biomarkers for treatment response is crucial for the development of effective interventions. Voice-b...

Altered entropy modulation in bipolar disorder: EEG entropy measures during steady-state auditory entrainment.

BACKGROUND: Non-linear neural dynamics reflect the inherent complexity of brain activity and are increasingly recognized as important indicators of ne...

Predictive Accuracy of Natural Language Processing Extracted 3-Step Theory of Suicide Factor Scores Derived From Veterans' Clinical Progress Notes.

OBJECTIVES: To compare predictive accuracy of 3-step theory of suicide (3ST) factor scores derived from natural language processing of Veterans Health...

Powering the future: advances, challenges, and sustainability of polymer electrolytes in lithium-sulfur batteries.

Lithium-sulfur (Li-S) batteries offer a transformative theoretical energy density (∼2600 Wh kg-1), positioning them as strong candidates for next-gene...

Neurocognitive and Social Cognitive Predictors of Adolescent Major Depressive Disorder: A Machine Learning Classification Study.

Background/aimThis study aimed to investigate whether machine learning (ML) algorithms could accurately differentiate adolescents with Major Depressiv...

Simplifying Depression Diagnosis: Single-Channel EEG and Deep Learning Approaches.

Major depressive disorder (MDD) or depression is a chronic mental illness that significantly impacts individuals' well-being and is often diagnosed at...

Psychopathology profiles and longitudinal correlates of nonsuicidal self-injury in youth: a machine-learning approach.

Nonsuicidal self-injury (NSSI) in youth is clinically heterogeneous. We aimed to identify distinct psychopathology-based profiles among children and a...

An exploratory randomized controlled trial of an AI-enabled mental health intervention for generalized anxiety.

Generalized Anxiety Disorder (GAD) is prevalent and often co-occurs with depression, contributing to significant disability and healthcare burden. Alt...

Prediction of anti-epileptic drug response of patients based on peripheral blood RNA profiles and machine learning.

OBJECTIVE: In this study, we aimed to develop a method for predicting the response of patients to three commonly used anti-epileptic drugs (AEDs), nam...

Predicting Depression Risk Among Chinese College Students From Childhood Adversity and Recent Stress Exposure Using Interpretable Machine Learning.

Previous research has shown that both early-life stressors (e.g., adverse childhood experiences) and recent stress exposure (e.g., recent life events)...

Factors linked to depressive symptoms in obsessive-compulsive disorder: a machine learning and network analysis from China OCD Cohort (COCC).

Classification and discrimination of emotion dysregulation disorders using machine learning.

Attention-deficit/hyperactivity (ADHD), bipolar (BD) and borderline personality (BPD) disorders are severe psychiatric illnesses often presenting with...

From non-specific biomarker to targeted action: transdiagnostic and sex-specific drivers of high-CRP status in severe mental illness across the FondaMental Advanced Centers of Expertise (FACE) cohorts.

BACKGROUND AND OBJECTIVES: Low-grade systemic inflammation contributes to the pathophysiology of severe mental illness (SMI) in a substantial subset o...

Constructing fine-grained subcortical atlases with connectional consensus graph representation learning.

Objective.The complex internal organization of subcortical structures forms the foundation of critical neural circuits that support sensorimotor proce...

Gut microbiome signatures associated with depression and obesity.

UNLABELLED: Depression and obesity are highly comorbid and likely involve common risk factors and pathophysiological mechanisms, which could crosslink...

Voice-based machine learning for rapid screening of bipolar disorder and major depressive disorder in children and adolescents: a robust and low-complexity diagnostic model.

BACKGROUND: Major depressive disorder (MDD) and bipolar disorder (BD) are psychiatric disorders that seriously impact physical and mental health. They...

A multilayered integrated analysis of insomnia-related genes ATG7 and JAK2 in the autophagy-inflammation mechanism and clinical implications in major depressive disorder.

OBJECTIVE: Insomnia is widely recognized as a key risk factor for major depressive disorder (MDD). However, the potential molecular mechanisms and the...

Designing Poly(ionic liquid)s as High-Performance LiFePO4 Binders via Mechanistic Study and ML-Assisted Structure-Property Analysis.

Conventional LiFePO4 (LFP) cathodes employing poly(vinylidene fluoride) (PVDF) as binder exhibit relatively stable cycling performance but suffer from...