Bipolar Disorder

Monitoring airline pilot mental health: a 3PM framework utilising digital phenotyping and AI.

The aeromedical certification of commercial airline pilots relies on periodic, self-disclosure-dependent assessments. However, this reactive model lacks the temporal resolution required to capture the gradual behavioural and physiological perturbations preceding an overt mental health crisis. Concurrently, anonymous epidemiological surveys consistently document subclinical depressive symptoms, ins...

Cerebellar gray matter volume difference in first-episode bipolar and unipolar depression.

BACKGROUND: Early differential diagnosis of bipolar disorder (BD) and unipolar depression (UD) remains a major clinical challenge, especially during the initial depressive episode. This study aimed to investigate whether cerebellar gray matter volume could serve as a potential neuroimaging biomarker to distinguish BD from UD at an early stage. METHODS: Structural MRI data were obtained from 42 pat...

A multimodal fNIRS-based machine learning model for symptom assessment and treatment response prediction in schizophrenia.

OBJECTIVE: Predicting early symptom severity and treatment response in schizophrenia is crucial for selecting optimal therapeutic strategies. This stu...

The effect of robot-based interventions on depression in older adults with cognitive impairment: A systematic review and meta-analysis.

OBJECTIVE: To assess the effectiveness of robot-based interventions in improving depressive symptoms among older adults with cognitive impairment, and...

Rhythms of mood: Bidirectional regulation of molecular clocks and neurotransmission in affective disorders.

Mood disorders, primarily major depressive and bipolar disorder, are characterized by significant neurochemical dysregulation and disturbances in biol...

Non-European migrants with schizophrenia spectrum disorders in Swiss forensic and general psychiatric care facilities - A comparative study using machine learning.

Personal history of migration poses an important risk factor for schizophrenia spectrum disorders (SSD), which are also associated with a higher rate ...

Interpretable depressive symptoms screening via statistical reasoning-augmented large language models using wearable and environmental data.

Early assessment of depressive symptoms is essential for scalable and personalized mental health care. We developed a hybrid clinical decision support...

Generating imperceptible adversarial examples via low-frequency aware transfer attacks on battery management systems.

Despite the success of deep learning models for the state-of-health estimation of lithium-ion batteries in battery management systems, their susceptib...

Screening of molecular signatures from microRNA and mRNA expression profiling related to the efficacy of the antidepressant duloxetine and analysis of their regulatory relationship.

Previous clinical studies have reported that not all depressed patients respond to antidepressants. Therefore, finding potential predictive molecular ...

Unraveling defect-mediated ion transport behavior in anti-perovskite solid-state electrolytes via machine learning molecular dynamics simulations.

Anti-perovskite (AP) solid-state electrolytes (SSEs) have emerged as promising candidates for high-safety solid-state batteries due to their wide elec...

User Experience and Early Clinical Outcomes of a Mental Wellness Chatbot for Depression and Anxiety: Pilot Evaluation Mixed Methods Study.

BACKGROUND: Artificial intelligence-powered conversational agents (ie, chatbots) are increasingly popular outlets for users seeking psychological supp...

Machine learning-driven time series analysis for SOH prediction of lithium-ion batteries.

Energy storage batteries are essential for stabilizing renewable energy systems and improving power grid efficiency. However, challenges such as capac...

Evaluating carbon efficiency across the lithium-ion battery industry using a SMOTE-augmented Super-SBM approach.

The lithium-ion battery (LIB) industry, a cornerstone of energy storage technology, is critical in the global transition towards low-carbon energy sys...

Development and validation of a precision treatment rules for first-line antipsychotic recommendations in first episode psychosis jointly incorporating effectiveness, side effects and patient preferences.

Selecting first-line antipsychotic medication for first episode of psychosis patients is a very challenging task requiring the clinicians to empirical...

Oral Health and Social Engagement of Older Adults: A Longitudinal Study.

OBJECTIVES: This study examines whether better oral health is associated with greater social engagement in later life and whether oral health and soci...

Acoustoelectric control of optoelectronic anisotropy for reconfigurable polarimetry.

Harnessing light polarization provides a powerful degree of freedom for optical communications, imaging, and sensing. Two-dimensional (2D) anisotropic...

Pollutant-Specific Pathways Linking Gaseous Air Pollution to Adolescent Depressive Symptoms: Direct and Sleep-Mediated Effects in a Population-Based Retrospective Cohort Study.

OBJECTIVE: This study aimed to examine associations between multiple gaseous air pollutants across different developmental periods and depressive in l...

Identifying treatment response classes to transcranial direct current stimulation (tDCS) from daily ecological momentary assessment (EMA) patterns in patients with depression.

IMPORTANCE: Transcranial direct current stimulation (tDCS) is known to be promising for depression, but heterogeneity across studies highlights the ne...

Evaluating Public Sentiment on Attention-Deficit/Hyperactivity Disorder and Autism Spectrum Disorder Compared With Other Mental Health Disorders From Posts on X (Formerly Known as Twitter): Longitudinal Analysis.

BACKGROUND: Neurodevelopmental disorders, especially attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), have seen a m...

Identification and independent validation of white matter subtypes in major depressive disorder and their role in predicting treatment response.

Major depressive disorder (MDD) is a complex psychiatric disorder characterized by diverse clinical profiles and variable treatment responses. Parsing...