Latest AI and machine learning research in bipolar disorder for healthcare professionals.
Electroencephalography (EEG) recordings are widely used in neuroscience to identify healthy individual brain rhythms and to detect alterations associated with various brain diseases. However, understanding the cellular origins of scalp EEG signals and their spatiotemporal changes during the resting state (RS) in humans remains challenging, as cellular-level recordings are typically restricted to a...
BACKGROUND: This study aimed to determine whether handwriting patterns are altered in individuals experiencing depressive episodes. Additionally, we developed a model for the recognition of major depressive disorder (MDD) based on electronic handwriting in psychological tasks.
BACKGROUND: Depression is associated with alterations in immuno-metabolic biomarkers, but it remains unclear whether these alterations are limited to ...
Sodium-ion batteries (SIBs) have emerged as a viable alternative to lithium-ion technologies, with carbon-based anodes playing a pivotal role in addre...
Microstructure often dictates materials performance, yet it is rarely treated as an explicit design variable because microstructure is hard to quant...
The study aimed to develop a predictive model using machine learning algorithms, providing healthcare professionals with a novel tool for assessing di...
BACKGROUND: Cognitive deficits are a central feature of schizophrenia for which there are not any established pharmacological treatments. Antipsychoti...
Parkinson's disease (PD) is a neurodegenerative disorder, manifesting with motor and non-motor symptoms. Depressive symptoms are prevalent in PD, af...
Generative diffusion models have achieved remarkable success in producing high-quality images. However, these models typically operate in continuous...
The global increase in the number of older people aged 65 and over is causing concern in healthcare and social systems. The lack of health and welfare...
IMPORTANCE: The diagnosis of schizophrenia and bipolar disorder is often delayed several years despite illness typically emerging in late adolescence ...
AIM: This study aimed to evaluate the effect of esketamine on perioperative anxiety and depressive symptoms, acute stress reaction, and serum neurotra...
The physics-based Doyle-Fuller-Newman (DFN) model, widely adopted for its precise electrochemical modeling, stands out among various simulation mode...
Major depressive disorder (MDD) impacts more than 300 million people worldwide, highlighting a significant public health issue. However, the uneven ...
Accurate prediction of lithium-ion battery lifespan is vital for ensuring operational reliability and reducing maintenance costs in applications lik...
Depression is a complex mental disorder characterized by a diverse range of observable and measurable indicators that go beyond traditional subjecti...
Battery degradation is a major challenge in electric vehicles (EV) and energy storage systems (ESS). However, most degradation investigations focus ...
Previous research has established type 2 diabetes mellitus as a significant risk factor for various disorders, adversely impacting human health. While...
The 3D microstructure of porous media, such as electrodes in lithium-ion batteries or fiber-based materials, significantly impacts the resulting mac...
Lithium-ion battery health management has become increasingly important as the application of batteries expands. Precise forecasting of capacity deg...