Latest AI and machine learning research in bipolar disorder for healthcare professionals.
The accuracy of grey-matter predictors of depression has remained limited. In this study, brain-based predictors of major depressive disorder (MDD) were trained using machine-learning (Best Linear Unbiased Predictors [BLUP]) and deep-learning (ResNet3D) techniques applied to high-dimensional (voxel-wise) grey-matter structure extracted from T1-weighted structural MRI. The training sample comprised...
The inherent instability of lithium metal with liquid electrolytes, as well as the performance constraints of typical solid electrolytes, has long shifted efforts to develop lithium metal batteries (LMBs). This review contends that the design approach is evolving from simply combining materials to designing multifunctional, network matrices. We critically investigate the development of cross-linke...
The rapid development of electric vehicles and large-scale energy storage is driving the requirements for lithium-ion batteries (LIBs) with high energ...
Error monitoring is crucial for inferring how controllable an environment is, and thus for estimating the value of control processes (metacontrol). In...
BACKGROUND: Major depressive disorder (MDD) is a neuro-immune, oxidative, and nitrosative stress (NIMETOX) disorder, in which peripheral immune-redox ...
BACKGROUND: Pediatric bipolar disorder(BD) is difficult to distinguish from other psychiatric disorders, a challenge which can result in delayed or in...
Artificial light at night (ALAN) has been classified as a significant environmental endocrine disruptor. Excessive exposure to ALAN has associated wit...
Mental health issues are surging in contemporary society, especially among adolescents and adults, harming well-being and social functioning. Objectiv...
Digital phenotyping promises to transform psychiatry by using multimodal, densely sampled data. However, its potential is hindered by the lack of focu...
Differentiating between bipolar disorder (BD) and schizophrenia (SZ) is challenging due to overlapping clinical symptoms and shared genetic risks, res...
INTRODUCTION: Depression frequently co-occurs with psychosis and is associated with poor outcomes. Early identification of patients at risk of persist...
In situ monitoring of lithium-ion battery thermal runaway is limited by the invasiveness and insufficient sensitivity of conventional thermometry. The...
Understanding electric-field-induced phase transitions is crucial for optimizing the ferroelectric and antiferroelectric properties of hafnium zirconi...
Psychiatry's metamorphosis continues to evolve over time as concepts of the brain's neuronal function and the complexity of the mind interact with rap...
IMPORTANCE: Depression most commonly first emerges during adolescence, making early prevention critical. While school-based mindfulness training (SBMT...
Research and development of non-aqueous electrolyte solutions are essential for practical advancement towards the production of high-energy lithium me...
The best predictor of a suicide attempt is a previous attempt, apart from psychiatric diagnoses also associated. Some studies found other indicators o...
To address the impending lithium supply crisis, membrane-based extraction from salt-lake brines has emerged as a pivotal area of research in the field...
BACKGROUND: Major depressive disorder (MDD) is a leading cause of global disability and poses a substantial public health burden. However, current dia...