Psychiatry

Blood urea nitrogen-to-lipid ratios are novel indices inversely associated with anxiety: Insights from NHANES.

BACKGROUND: Anxiety is a highly prevalent mental disorder linked to metabolic and renal dysregulation. Blood urea nitrogen (BUN) and lipid profiles have been associated with affective symptoms, but findings are inconsistent, indicating the limitations of the single indicator. Therefore, this study proposed novel BUN-to-lipid indicators and investigated their associations with anxiety. METHODS: We ...

The Future of Digital Mental Health: A Literature Review.

Digital mental health tools-including telehealth, mobile applications, wearable devices, machine learning, and artificial intelligence-are changing the way patients and providers manage mental health care. This review summarizes the current research findings of digital interventions on patient access to care, the factors impacting personalized care, and overall patient engagement. Gaps of knowledg...

A full-function memristive associative memory neural network circuit based on multi-frequency SRDP rule.

Previous studies on memristive associative neural network circuits have not sufficiently incorporated the effects of spike-rate-dependent plasticity (...

Cingulate atrophy as a shared structural basis for cognitive and functional brain impairments in GAD, PD, and OCD: Links to shared gene expression and treatment implications.

BACKGROUND: Structural brain deficits associated with generalized anxiety disorder (GAD), panic disorder (PD), and obsessive-compulsive disorder (OCD)...

Brain dynamics and depressive symptoms in young adults: Evidence from EEG.

BACKGROUND: Depression is a major public health concern, with a rising prevalence among adolescents and young adults. However, the neural mechanisms u...

Machine learning prediction of conduct problems in children using the longitudinal ABCD study.

BACKGROUND: Children with conduct problems are at elevated risk for negative psychosocial, educational, and behavioral outcomes. Identifying at-risk c...

Comorbid anxiety predicts lower odds of MDD improvement in a trial of smartphone-delivered interventions.

Comorbid anxiety disorders are common among patients with major depressive disorder (MDD), but their impact on outcomes of digital and smartphone-deli...

The similarities and differences of multiple chronic diseases risk factors across depressive symptoms trajectories among middle-aged and older Chinese adults: A 10-year longitudinal cohort study.

BACKGROUND: Depressive symptoms and multiple chronic diseases (MCDs) significantly contribute to the global disease burden among middle-aged and older...

Distinct electroencephalogram microstate in patients with methamphetamine use disorder and obsessive-compulsive disorder.

BACKGROUND: Electroencephalogram (EEG) microstates reflect momentary localized brain activity and may indicate spontaneous fluctuations within large-s...

Esflurbiprofen exerts a fast-onset antidepressant effect by blocking SERT-nNOS interaction.

Selective serotonin reuptake inhibitors (SSRIs) are characterized by delayed therapeutic onset largely due to their reliance on the desensitization of...

Characterizing and predicting refractory rumination in obsessive compulsive disorder.

Rumination is problematic for individuals with obsessive compulsive disorder (OCD), and yet, is not addressed in standard treatment for OCD. Further, ...

A novel potential biomarker panel to diagnose depression derived from big proteomic data.

BACKGROUND: There is still no clinical biomarker to diagnose depression. Given the complexity of a multifactorial disease like depression, a single bi...

Between Trust and Tension: Psychosocial Impact of AI Integration on Health Professionals' Wellbeing.

ObjectiveThis study explored health professionals' experiences of using Artificial Intelligence (AI) in healthcare with a particular focus on the pote...

Financial Well-Being in Older Adults: A Machine Learning Analysis of 47 Potential Predictors.

This study examined potential predictors of financial well-being in older adults. Data were drawn from the Health and Retirement Study, focusing on ps...

Predicting neurobehavioral outcomes in people with HIV.

BACKGROUND: This study identified complex, multidimensional, longitudinal biopsychosocial (BPS) phenotypes (MLBPSPs) in people with HIV (PWH) and eval...

Radiation Risk in 2D Mammography Screening: A Scoping Review of Modelling Strategies and Emerging AI Applications.

Breast cancer is the most commonly diagnosed cancer among women worldwide, and concerns regarding radiation exposure from mammography screening remain...

Classification of major depressive disorder using vertex-wise brain sulcal depth, curvature, and thickness with a deep and a shallow learning model.

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even...

Brain metabolic imaging with 18 F-PET-CT and machine-learning clustering analysis reveal divergent metabolic phenotypes in patients with amyotrophic lateral sclerosis.

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by significant clinicopathologic heterogeneity. Th...

Harnessing Machine Learning to Predict Nurse Turnover Intention and Uncover Key Predictors: A Multinational Investigation.

AIMS: To predict nurses' turnover intention using machine learning techniques and identify the most influential psychosocial, organisational and demog...

Probiotics, psychobiotics, and postbiotics: a therapeutic modality for the management of schizophrenia.

Schizophrenia is a debilitating, chronic neuropsychiatric disorder, a multifactorial disorder combining genetic, neurodevelopmental, immunological, an...