Latest AI and machine learning research in seizures for healthcare professionals.
OBJECTIVES: To create a classifier based on electroencephalography (EEG) to identify spinal cord inj...
OBJECTIVE: Constant changes in developing children's brains can pose a challenge in EEG dependant te...
The electroencephalogram (EEG) is the most prominent means to study epilepsy and capture changes in ...
Brain function has been proposed to arise as a result of the coordinated activity between distribute...
Seizure prediction has attracted growing attention as one of the most challenging predictive data an...
BACKGROUND: Artificial neural networks (ANNs) are one of the widely used classifiers in the brain-co...
In recent years, advanced neurocomputing and machine learning techniques have been used for Electroe...
Successful diagnosis and management of neurological dysfunction relies on proper communication betwe...
While biomedical ontologies have traditionally been used to guide the identification of concepts or ...
Although robot technology has been successfully used to empower people who suffer from motor disabil...
Functional brain network (FBN) has become very popular to analyze the interaction between cortical r...
OBJECTIVE: Focal cortical dysplasia (FCD) is a major pathology in patients undergoing surgical resec...
Identifying a core set of features is one of the most important steps in the development of an autom...
BACKGROUND: Responses to transcranial magnetic stimulation (TMS) are notoriously variable. Previous ...
This paper presents a novel algorithm (CVSTSCSP) for determining discriminative features from an opt...
Dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) require differential management despite...
The objective of this study was to introduce a new machine learning guided by outcome of resective e...
Neural mass models (NMMs) are increasingly used to uncover the large-scale mechanisms of brain rhyth...
OBJECTIVE: Brain-computer interface (BCI) refers to procedures that link the central nervous system ...
Automatic seizure detection is extremely important in the monitoring and diagnosis of epilepsy. The ...
In this paper, we present a multimodal emotion recognition framework called EmotionMeter that combin...