Bipolar Disorder

Who thrives against the odds? Mapping adolescent trait heterogeneity of emotional maltreatment effects with causal forests DML.

BACKGROUND: Emotional maltreatment (EM) during childhood and adolescence exerts lasting effects on psychopathology, yet individuals exposed to similar adversity often show divergent outcomes. OBJECTIVE: To examine heterogeneous effects of cumulative EM on young-adult psychopathology and identify adolescent strengths associated with resilient subgroup among adolescents with high EM. PARTICIPANTS AN...

EXPRESS: Static and dynamic perspective on brain activity and functional connectivity alternations in the comorbidity of chronic pain and depression: An fMRI study in rats.

BACKGROUND: Clinically, chronic pain and depression often coexist in multiple diseases and reciprocally reinforce each other, which greatly escalates the difficulty of treatment. The alteration in neural networks underlying the chronic pain/depression comorbidity remains unclear. METHODS: Spared nerve injury (SNI) was performed to establish a rat model of comorbidity of chronic pain and depression...

Digital and AI-enhanced psychosocial interventions in breast cancer patients: a systematic review and meta-analysis.

PURPOSE: Digital and AI-supported psychosocial interventions are increasingly implemented to address psychological distress among women with breast ca...

Impact of a personalized antidepressant prescription using genetics, socio-demographic and clinical data in major depressive disorder patients: A clinical study.

BACKGROUND: Major depressive disorder (MDD) is common and disabling, and antidepressant selection often follows a trial-and-error process. Predictix i...

Multimodal fusion of speech and PHQ-9 for machine learning-based adolescent depression screening.

BACKGROUND: Traditional screening for adolescent depression primarily relies on self-reported symptoms. However, this method is vulnerable to under-re...

Deep learning-based differential diagnosis of major depression and bipolar disorder using microglia-cellular sensors and patient-derived small extracellular vesicles.

Upcycling Industrial Wastewater to Three-Dimensional Porous Cu4(OH)6FCl Nanosheets as Anode for High-Performance Lithium-Ion Batteries.

With the vigorous development of artificial intelligence and the semiconductor industry, the treatment of a mass of copper- and fluorine-containing in...

Predictive neuroimaging biomarkers of major depressive disorder treatment response: An umbrella review.

Major depressive disorder (MDD) is a heterogeneous condition with varied responses to pharmacological, psychotherapeutic, and neuromodulation interven...

Machine learning-based risk classification of depressive symptoms among patients with hearing loss: evidence from the Health and Retirement Study (HRS).

BACKGROUND: Depression is a common and debilitating condition among individuals with hearing loss, substantially impairing patients' quality of life. ...

Multimorbidity and major adverse cardiovascular events in antipsychotic users: Time-to-event prediction by explainable machine learning.

Antipsychotic treatment is associated with higher risk of major adverse cardiovascular events (MACEs), and risk may vary by multimorbidity and concomi...

Bipolar disorder relapse detection and prediction using smartwatches. A pilot study for machine learning models using anomaly detection methods.

BACKGROUND: Bipolar disorder (BD) is a chronic mental illness with recurrent mood episodes, with up to 70% of patients relapsing within two years. Ear...

Prediction model for frailty risk in ischemic stroke patients: Application and validation of support vector machines and nomograms.

This study aimed to develop a prediction model based on nomograms and support vector machines (SVM) to assess frailty risk in ischemic stroke patients...

Machine learning-assisted discovery of outside-in structure Ni-rich cathode with high performance.

Ni-rich oxides have emerged as leading cathode candidates for lithium-ion batteries because of high specific energy, lower cost, and improved sustaina...

Objective diagnosis and treatment outcome prediction in major depressive disorder based on a machine learning framework with dried-serum NIRS digital biomarkers.

The impact of the radical urbanization index on depression risk among middle-aged and elderly Chinese: Evidence from a large-scale cross-sectional study.

BACKGROUND: Rapid urbanization in China, while boosting socioeconomic development, has triggered "radical urbanization" characterized by land expansio...

Using natural language processing to assess MDD psychotherapy patterns among Veterans Affairs patients with suicide risk.

Major depressive disorder (MDD) is a leading risk factor for suicide. Within the US Department of Veterans Affairs (VA), psychotherapy is widely used ...

Speech analysis for differentiating bipolar disorder and major depressive disorder during euthymic states.

Classification of depressed and non-depressed MCI and non-depressed cognitively normal individuals using resting-state metrics: A multi-group study with machine learning and graph reinforcement learning.

Depressive symptoms frequently co-occur in individuals with Mild Cognitive Impairment (MCI) and are thought to accelerate neurodegenerative progressio...

Machine Learning Approaches to Identify Physical, Psychological, and Social Predictors of Worsening Frailty Transitions Among Community-Dwelling Older Adults: A Longitudinal Cohort Study.

BACKGROUND: Frailty poses a significant challenge to aging societies, with increasing attention being paid to the concept of frailty transitions. Wors...

Explainable Deep Learning-Guided Screening of LiNO3-Based Molten-Salt Phase Change Materials for Lithium-Ion Battery Safety.

LiNO3-based high-temperature phase change materials (PCMs), owing to their specific advantages, e.g., high thermal stability and high latent heat, hav...