Latest AI and machine learning research in seizures for healthcare professionals.
Epilepsy affects over 50 million people globally. Electroencephalography is critical for epilepsy di...
Accurate seizure and epilepsy diagnosis remains a challenging task due to the complexity and variabi...
. The instability of the EEG acquisition devices may lead to information loss in the channels or fre...
Spiking neural networks (SNNs) are receiving increased attention because they mimic synaptic connect...
OBJECTIVES: We set out to develop a machine learning model capable of distinguishing patients presen...
Interictal Epileptiform Discharges (IED) and High Frequency Oscillations (HFO) in intraoperative ele...
To enhance deep learning-based automated interictal epileptiform discharge (IED) detection, this stu...
Predicting the potential for recovery of motor function in stroke patients who undergo specific reha...
Parkinson's disease (PD) is a progressive neurodegenerative disorder affecting the quality of life o...
Transfer learning (TL) has demonstrated its efficacy in addressing the cross-subject domain adaptati...
Anaesthesia, crucial to surgical practice, is undergoing renewed scrutiny due to the integration of ...
EEG signal classification using Riemannian manifolds has shown great potential. However, the huge co...
PURPOSE: Focal cortical dysplasias (FCDs) are a leading cause of drug-resistant epilepsy. Early dete...
In medicine, abnormalities in quantitative metrics such as the volume reduction of one brain region ...
Our ability to measure time is vital for daily life, technology use, and even mental health; however...
Depression is a serious mental health disorder affecting millions of individuals worldwide. Timely a...
Developing an electroencephalography (EEG)-based brain-computer interface (BCI) system is crucial to...
Seizure events can manifest as transient disruptions in the control of movements which may be organi...
Artificial intelligence (AI) has been supporting our digital life for decades, but public interest i...
The problem of multi-class classification is always a challenge in the field of EEG (electroencephal...
OBJECTIVE: Despite advances, analysis and interpretation of EEG still essentially rely on visual ins...