Latest AI and machine learning research in seizures for healthcare professionals.
Identifying new anti-seizure medications (ASMs) is difficult due to limitations in animal-based assa...
Denoising artifacts, such as noise from muscle or cardiac activity, is a crucial and ubiquitous conc...
BACKGROUND: The proportion of traffic accidents caused by fatigue driving is increasing year by year...
Previous deep learning-based brain network research has made significant progress in understanding t...
BACKGROUND: Electroencephalogram (EEG) microstates, which reflect large-scale resting-state networks...
Accurate recognition and classification of motor imagery electroencephalogram (MI-EEG) signals are c...
Research on emotion recognition is an interesting area because of its wide-ranging applications in e...
EEG signals exhibit spatio-temporal characteristics due to the neural activity dispersion in space o...
With the advancement of artificial intelligence technology, more and more effective methods are bein...
PURPOSE: In the context of EEG-based emotion recognition tasks, a conventional strategy involves the...
Approximately 30%-40% of epilepsy patients do not respond well to adequate anti-seizure medications ...
Epilepsy, a neurological disorder causing recurring seizures, is often studied in zebrafish by expos...
The objective of this study is to assess the potential of a transformer-based deep learning approach...
Parkinson Disease (PD) is a complex neurological disorder attributed by loss of neurons generating d...
PURPOSE: Advancements in Machine Learning (ML) techniques have revolutionized diagnosing and monitor...
OBJECTIVES: To develop a predicted algorithm for drug-resistant epilepsy (DRE) in newly diagnosed te...
. Machine learning has enhanced the performance of decoding signals indicating human behaviour. Elec...
Electroencephalography (EEG) is invaluable in the management of acute neurological emergencies. Char...
Electroencephalography microstates (EEG-MS) show promise to be a neurobiological biomarker in stroke...
OBJECTIVE: This study aimed to establish an optimal model based on machine learning (ML) to predict ...
Anomalous chromosomes are the cause of genetic diseases such as cancer, Alzheimer's, Parkinson's, ep...