Epilepsy in adults
Epilepsy is one of the most common serious brain conditions, affecting over 70 million
people worldwide. Its incidence has a bimodal distribution with the highest risk in infants and …
people worldwide. Its incidence has a bimodal distribution with the highest risk in infants and …
Neutrophil to lymphocyte ratio in epilepsy: a systematic review
This study was conducted to summarize the results of studies investigating the role of
neutrophil to lymphocyte ratio (NLR) in epilepsy. The search was conducted on PubMed …
neutrophil to lymphocyte ratio (NLR) in epilepsy. The search was conducted on PubMed …
An automated system for epilepsy detection using EEG brain signals based on deep learning approach
Epilepsy is a life-threatening and challenging neurological disorder, which is affecting a
large number of people all over the world. For its detection, encephalography (EEG) is a …
large number of people all over the world. For its detection, encephalography (EEG) is a …
[BOOK][B] Epilepsy: a public health imperative
World Health Organization - 2019 - apps.who.int
Epilepsy is a brain disease characterized by abnormal electrical activity causing seizures or
unusual behaviour, sensations and sometimes loss of awareness. It carries neurological …
unusual behaviour, sensations and sometimes loss of awareness. It carries neurological …
Learning robust features using deep learning for automatic seizure detection
We present and evaluate the capacity of a deep neural network to learn robust features from
EEG to automatically detect seizures. This is a challenging problem because seizure …
EEG to automatically detect seizures. This is a challenging problem because seizure …
A deep convolutional neural network method to detect seizures and characteristic frequencies using epileptic electroencephalogram (EEG) data
Background: Diagnosing epileptic seizures using electroencephalogram (EEG) in
combination with deep learning computational methods has received much attention in …
combination with deep learning computational methods has received much attention in …
Adaptive boost LS-SVM classification approach for time-series signal classification in epileptic seizure diagnosis applications
Epileptic seizures are characterised by abnormal neuronal discharge, causing notable
disturbances in electrical activities of the human brain. Traditional methods based on …
disturbances in electrical activities of the human brain. Traditional methods based on …
A scheme combining feature fusion and hybrid deep learning models for epileptic seizure detection and prediction
J Zhang, S Zheng, W Chen, G Du, Q Fu, H Jiang - Scientific Reports, 2024 - nature.com
Epilepsy is one of the most well-known neurological disorders globally, leading to
individuals experiencing sudden seizures and significantly impacting their quality of life …
individuals experiencing sudden seizures and significantly impacting their quality of life …
Effect of probiotic supplementation on seizure activity and cognitive performance in PTZ-induced chemical kindling
Epilepsy is one of the most common neurological disorders that severely affect life quality of
many people worldwide. Ion transport in the neuronal membrane, inhibitory–excitatory …
many people worldwide. Ion transport in the neuronal membrane, inhibitory–excitatory …
Epileptic seizure detection in EEG using mutual information-based best individual feature selection
Epilepsy is a group of neurological disorders that affect normal brain activities and human
behavior. Electroencephalogram based automatic epileptic seizure detection has significant …
behavior. Electroencephalogram based automatic epileptic seizure detection has significant …