Latest AI and machine learning research in seizures for healthcare professionals.
Granger causality (GC) effective connectivity (EC) calculated from electroencephalogram (EEG) signal...
Integrating prior knowledge of neurophysiology into neural network architecture enhances the perform...
The contemporary diagnosis of Major Depressive Disorder (MDD) primarily relies on subjective assessm...
Seizures in electroencephalogram (EEG) data constitute a special case of sub-sequence anomalies in m...
In this paper, a hybrid CNN-BiLSTM model for EEG-based emotion detection system is presented. The pr...
PURPOSE: Focal cortical dysplasia (FCD) is a common cause of pharmacoresistant epilepsy. However, it...
Transfer learning, a technique commonly used in generative artificial intelligence, allows neural ...
The automatic classification of medical time series signals, such as electroencephalogram (EEG) an...
Reconstructing visual stimuli from EEG signals is a crucial step in realizing brain-computer inter...
Accurately localizing the brain regions that triggers seizures and predicting whether a patient wi...
Recent advancements in Large Language Models have inspired the development of foundation models ac...
Recent studies have demonstrated that the representations of artificial neural networks (ANNs) can e...
Data augmentation has been demonstrated to improve the classification accuracy of deep learning mode...
Reconstructing and understanding dynamic visual information (video) from brain EEG recordings is c...
Human preference research is a significant domain in psychology and psychophysiology, with broad a...
Aperiodic neural activity has been the subject of intense research interest lately as it could ref...
Aperiodic neural activity has been the subject of intense research interest lately as it could ref...
Feature engineering for generalized seizure detection models remains a significant challenge. Rece...
Functional connectivity (FC) analyses of intracranial EEG (iEEG) signals can potentially improve the...
Electroencephalography (EEG) is essential for studying infant brain activity but is highly susceptib...
Pretrained generative models have opened new frontiers in brain decoding by enabling the synthesis...