Epileptic seizure prediction using deep transformer model
The electroencephalogram (EEG) is the most promising and efficient technique to study
epilepsy and record all the electrical activity going in our brain. Automated screening of …
epilepsy and record all the electrical activity going in our brain. Automated screening of …
[HTML][HTML] EpilepsyNet: Novel automated detection of epilepsy using transformer model with EEG signals from 121 patient population
Background Epilepsy is one of the most common neurological conditions globally, and the
fourth most common in the United States. Recurrent non-provoked seizures characterize it …
fourth most common in the United States. Recurrent non-provoked seizures characterize it …
Deep learning based efficient epileptic seizure prediction with EEG channel optimization
R Jana, I Mukherjee - Biomedical Signal Processing and Control, 2021 - Elsevier
A seizure is an unstable situation in epilepsy patients due to excessive electrical discharge
by brain cells. An efficient seizure prediction method is required to reduce the lifetime risk of …
by brain cells. An efficient seizure prediction method is required to reduce the lifetime risk of …
Epileptic seizure prediction using deep neural networks via transfer learning and multi-feature fusion
Z Yu, L Albera, R Le Bouquin Jeannes… - … journal of neural …, 2022 - World Scientific
Epilepsy is one of the most common neurological diseases, which can seriously affect the
patient's psychological well-being and quality of life. An accurate and reliable seizure …
patient's psychological well-being and quality of life. An accurate and reliable seizure …
Epileptic seizures prediction using deep learning techniques
Epilepsy is a very common neurological disease that has affected more than 65 million
people worldwide. In more than 30% of the cases, people affected by this disease cannot be …
people worldwide. In more than 30% of the cases, people affected by this disease cannot be …
An end-to-end deep learning approach for epileptic seizure prediction
An accurate seizure prediction system enables early warnings before seizure onset of
epileptic patients. It is extremely important for drug-refractory patients. Conventional seizure …
epileptic patients. It is extremely important for drug-refractory patients. Conventional seizure …
Seizure prediction based on transformer using scalp electroencephalogram
J Yan, J Li, H Xu, Y Yu, T Xu - Applied Sciences, 2022 - mdpi.com
Epilepsy is a chronic and recurrent brain dysfunction disease. An acute epileptic attack will
interfere with a patient's normal behavior and consciousness, having a great impact on their …
interfere with a patient's normal behavior and consciousness, having a great impact on their …
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 …
Deep learning models for predicting epileptic seizures using iEEG signals
O Ouichka, A Echtioui, H Hamam - Electronics, 2022 - mdpi.com
Epilepsy is a chronic neurological disease characterized by a large electrical explosion that
is excessive and uncontrolled, as defined by the world health organization. It is an anomaly …
is excessive and uncontrolled, as defined by the world health organization. It is an anomaly …
[PDF][PDF] Epileptic seizure detection using deep learning through min max scaler normalization
B Deepa, K Ramesh - Int J Health Sci (Qassim), 2022 - pdfs.semanticscholar.org
Epileptic seizure detection and prediction are significantly sought-after research currently
because robust algorithms are available. Machine learning and deep learning have allowed …
because robust algorithms are available. Machine learning and deep learning have allowed …