Psychiatry

Bipolar Disorder

Latest AI and machine learning research in bipolar disorder for healthcare professionals.

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Exosomal microRNA signatures in youth at clinical high risk for bipolar disorder.

INTRODUCTION: Individuals at clinical high risk for bipolar disorder (CHR-BD) experienced insufficie...

Unveiling the invisible: How cutting-edge neuroimaging transforms adolescent depression diagnosis.

Yu 's study has advanced the understanding of the neural mechanisms underlying major depressive diso...

Ethical and social issues in prediction of risk of severe mental illness: a scoping review and thematic analysis.

BACKGROUND: Over the last decade, there has been considerable development in precision psychiatry, e...

Grain boundary amorphization as a strategy to mitigate lithium dendrite growth in solid-state batteries.

Solid-state lithium metal batteries using garnet-type LiLaZrO electrolytes hold immense promise for ...

Subtyping first-episode psychosis based on longitudinal symptom trajectories using machine learning.

Clinical course after first episode psychosis (FEP) is heterogeneous. Subgrouping and predicting lon...

Degradation studies on lurasidone hydrochloride using validated reverse phase HPLC and LC-MS/MS.

1. The research aims to develop and validate a stability-indicating reverse phase high-performance l...

Improved serotonin neuron-specific viral vectors applicable for optogenetic manipulation and recording.

Serotonin neurons are central to the pathophysiology and therapeutics of mental disorders, including...

Association of Physical Activity from Wearable Devices and Chronic Disease Risk: Insights from the All of Us Research Program.

Physical activity is a modifiable factor influencing chronic disease risk. Previous studies often re...

AI-driven early diagnosis of specific mental disorders: a comprehensive study.

One of the areas where artificial intelligence (AI) technologies are used is the detection and diagn...

Uni-Electrolyte: An Artificial Intelligence Platform for Designing Electrolyte Molecules for Rechargeable Batteries.

Electrolytes are an essential part of rechargeable batteries, such as lithium batteries. However, el...

A depression detection approach leveraging transfer learning with single-channel EEG.

Major depressive disorder (MDD) is a widespread mental disorder that affects health. Many methods co...

FIB-SEM: Emerging Multimodal/Multiscale Characterization Techniques for Advanced Battery Development.

The advancement of battery technology necessitates a profound understanding of the physical, chemica...

Predictive modeling of response to repetitive transcranial magnetic stimulation in treatment-resistant depression.

Identifying predictors of treatment response to repetitive transcranial magnetic stimulation (rTMS) ...

Machine learning for predicting medical outcomes associated with acute lithium poisoning.

The use of machine learning algorithms and artificial intelligence in medicine has attracted signifi...

Specific expression and common potential therapeutic drugs in different brain regions of major depressive disorder patients: bioinformatics analysis.

Major depressive disorder (MDD) is a prevalent and debilitating mental health condition characterize...

Deciphering failure paths in lithium metal anodes by electrochemical curve fingerprints.

Understanding anode failure mechanisms in lithium metal batteries (LMBs) is crucial for their use in...

Data-Knowledge-Dual-Driven Electrolyte Design for Fast-Charging Lithium Ion Batteries.

Electric vehicles (EVs) starve for minutes-level fast-charging lithium-ion batteries (LIBs), while t...

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