Bipolar Disorder

Compact Modeling of Pd-MoS2 Self-rectifying RRAM based on modulated Schottky barrier equation.

The rapid growth of artificial intelligence computing has intensified the demand for energyefficient hardware accelerators capable of large-scale matrix-vector multiplication. Resistive random-access memory has attracted significant interest for such applications due to its analog weight storage capability and compatibility with crosspoint array architectures. However, the sneak-path current remai...

Which machine learning algorithms are best at predicting eating disorder tendencies among nursing students in China?

BACKGROUND: Nursing students are at high risk for developing eating disorders (ED). However, methods for identifying ED tendencies within this group remain underexplored. PURPOSE: This study aims to develop and validate machine learning-based models for predicting ED tendencies among nursing students. METHODS: A cross-sectional study was conducted with a sample of nursing students in mainland Chin...

Altered thalamic subregional connectivity with default mode and frontoparietal networks in adolescents with depression.

BACKGROUND: The thalamus plays a pivotal role in the pathophysiology of adolescent depression, with its subregions showing functional heterogeneity. A...

Molecularly Engineered Wing-Shaped Azobenzene Memristors for Logic-in-Memory and Edge Visual Intelligence.

Organic molecular resistive memory offers a promising platform to overcome the von Neumann bottleneck. Here, we report four symmetric azobenzene-based...

Machine-Learning Framework for Designing Stable Interfaces in All-Solid-State Lithium-Ion Batteries.

All-solid-state lithium-ion batteries are promising next-generation energy-storage systems, but interfacial instability between cathodes and solid ele...

Distinct and Shared Molecular Mechanisms Underlie Morphological-Functional Overcoupling and Undercoupling in Major Depressive Disorder.

BACKGROUND: Major depressive disorder (MDD) exhibits significant heterogeneity in alterations of brain morphology and function, however, the potential...

Expression patterns of risk genes associated with three evolutionarily relevant syndromes in rhesus macaque and human brains.

Depressive disorder (DD), Alzheimer's disease (AD), and schizophrenia (SZ) are evolutionarily relevant traits that disrupt neural networks supporting ...

Efficient epileptic seizure prediction using single channel EEG signal and knowledge distillation on deep neural networks.

Epilepsy is a common neurological disease, and in some patients, abnormal changes in brain activity typically begin before the onset of a seizure. Ele...

Discrimination of generalized anxiety and major depressive disorders by machine learning of resting-state functional MRI.

OBJECTIVE: To address the clinical difficulty of differentiating Generalized Anxiety Disorder (GAD) from Major Depressive Disorder (MDD), this study a...

Circadian Rhythm Stabilization App to Prevent Mood Episode Recurrence in Patients With Mood Disorders: A Multicenter, Double-Blind, Sham-Controlled, Randomized Clinical Trial.

OBJECTIVE: Preventing recurrence is essential for improving the clinical course of major depressive disorder (MDD) and bipolar disorder (BD). The auth...

Supporting Student Mental Health With the Safespace Generative AI Chatbot: Mixed Methods Feasibility Study.

BACKGROUND: Generative artificial intelligence (GenAI) chatbots have the potential to provide personalized mental health support to individuals at sca...

Comprehensive analysis of interactions between brain aging and late-onset psychoses using heuristic mapping models.

BACKGROUND: Advanced brain aging is closely associated with late-onset psychoses, including bipolar disorder(BD), schizophrenia(SP), and major depress...

Using ChatGPT for thematic analysis of qualitative interviews in cultural research: a methodological investigation.

OBJECTIVE: The use of artificial intelligence (AI) tools in clinical and psychotherapy research is gaining increasing attention. This study explores t...

Embodied movement markers of alliance ruptures in psychotherapy: A machine learning study.

OBJECTIVE: Alliance ruptures are central to psychotherapy process and outcome, yet therapists often fail to detect them in real time, particularly wit...

Redefining LiF as a Nanostructured Building Block for Interphase Engineering in Lithium Metal Batteries.

Lithium metal batteries (LMBs) are regarded as promising next-generation energy storage systems due to their high theoretical capacity and low reducti...

AI for battery-accelerated discovery of high-voltage electrolytes for advanced lithium batteries.

As lithium batteries advance toward higher energy densities, developing electrolytes that remain stable under high-voltage conditions has become a cri...

A Physics-Guided Machine Learning Framework Enabling Interpretable and Transferable Cascade Reactor Modeling: Application to Metal Recovery Process.

Cascade reactors are vital for separation and purification processes such as metal recovery and wastewater treatment, owing to their enhanced reaction...

Atomic Origins of Ultrahigh-Voltage Failure in LiCoO2 Cathodes.

Pushing lithium cobalt oxide (LCoO2) toward extremely high-voltage operation up to 5V is critical to boosting a battery's energy density for future co...

The role of metabolic health in neurostructural and cognitive alterations in bipolar disorders.

BACKGROUND: Bipolar disorders (BD) rank among the most disabling conditions, affecting millions worldwide. Cognitive impairment in BD is linked with b...

The Digital Mirror: Clinical Potentials and Relational Risks of Generative AI in Mental Health Interventions.

PURPOSE OF REVIEW: This review explores the rapidly evolving integration of Generative Artificial Intelligence (GenAI) in mental health care. It aims ...