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
S Hosseini, AME Mofrad, P Mokarian… - Mediators of …, 2022 - Wiley Online Library
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 …
[图书][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
P Thodoroff, J Pineau, A Lim - Machine learning for …, 2016 - proceedings.mlr.press
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 …
[HTML][HTML] Weak supervision as an efficient approach for automated seizure detection in electroencephalography
Automated seizure detection from electroencephalography (EEG) would improve the quality
of patient care while reducing medical costs, but achieving reliably high performance across …
of patient care while reducing medical costs, but achieving reliably high performance across …
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 …