Alzheimer's disease (AD) is the leading form of dementia worldwide. AD disrupts neuronal
pathways and thus is commonly viewed as a network disorder. Many studies demonstrate …

Previous studies showed that entrainment of light flicker at low gamma frequencies provided
neuroprotection in mouse models of Alzheimer's disease (AD) and stroke. The current study …

Graph neural network (GNN) models are increasingly being used for the classification of
electroencephalography (EEG) data. However, GNN-based diagnosis of neurological …

Among electroencephalogram (EEG) signal emotion recognition methods based on deep
learning, most methods have difficulty in using a high-quality model due to the low resolution …

Background Alzheimer's disease can be diagnosed through various clinical methods.
Among them, electroencephalography has proven to be a powerful, non-invasive …

People around the globe are suffering from different types of brain–heart disorders. Early
detection of these disorders may increase the lifespan of humans. Numerous inherited and …

Alzheimer's disease (AD) is a chronic neurodegenerative disease. Early diagnosis are very
important to timely treatment and delay the progression of the disease. In the past decade …

Son on yılda, yapay zekâ (YZ) ve makine öğrenimi (MÖ) kullanımlarında bir artış
görülmüştür. MÖ alanındaki son gelişmeler, farklı alanlar için elektroensefalografinin (EEG) …

Background Alzheimer's disease (AD) is a common neurodegenerative dementia,
characterized by abnormal dynamic functional connectivity (DFC). Traditional DFC analysis …

Energy landscape analysis is a data‐driven method to analyse multidimensional time series,
including functional magnetic resonance imaging (fMRI) data. It has been shown to be a …