Latest AI and machine learning research in neurology for healthcare professionals.
Alzheimer's disease (AD) presents a critical global health challenge, with current therapies offerin...
Current evidence for predictive models of post-stroke depression (PSD) risk based on machine learnin...
The regulation of energy homeostasis is an essential function of every living organism. In mammals a...
Implementing Leaky Integrate-and-Fire (LIF) neurons in hardware is poised to enable the creation of ...
BackgroundSex differences in Alzheimer's disease (AD) progression offer insights into pathogenesis a...
The degeneration of midbrain dopamine (DA) neurons disrupts the neural control of natural behavior, ...
Chemotherapy-induced peripheral neuropathy (CIPN) is a common and debilitating adverse effect of ca...
Artificial Intelligence has shown great promise in healthcare, particularly in non-invasive diagnost...
Neuromorphic computing aims to mimic both the function and structure of biological neural networks t...
Spiking neural networks (SNNs) are biologically more plausible and computationally more powerful tha...
Reconstructing brain sources is a fundamental challenge in neuroscience, crucial for understanding b...
Electroencephalography (EEG) has evolved into an indispensable tool in pediatric epilepsy, fundament...
Hypnosis, traditionally studied as a psychological phenomenon, is increasingly explored through elec...
Artificial synaptic devices that mimic neuromorphic signal processing hold great promise for bioelec...
Electroencephalography (EEG) signals based emotion brain computer interface (BCI) is a significant f...
Alzheimer's disease (AD) biomarkers (Aβ42 or Tau 181) have high diagnostic performance. However, whe...
Epilepsy is a multifaceted and heterogenous neurological disorder that affects an estimated 70 milli...
OBJECTIVE: Stroke is a leading cause of long-term disability, significantly impacting patients' mobi...
To investigate the associations between both age and the hemoglobin glycation index (HGI) and the 30...
Accurate and early diagnosis of Alzheimer's Disease (AD) is crucial for timely interventions and tre...
OBJECTIVE: This work presents xEEGNet, a novel, compact, and explainable neural network for EEG data...