Scalp EEG classification using deep Bi-LSTM network for seizure detection
Automatic seizure detection technology not only reduces workloads of neurologists for
epilepsy diagnosis but also is of great significance for treatments of epileptic patients. A …
epilepsy diagnosis but also is of great significance for treatments of epileptic patients. A …
Automatic seizure detection using fully convolutional nested LSTM
The automatic seizure detection system can effectively help doctors to monitor and diagnose
epilepsy thus reducing their workload. Many outstanding studies have given good results in …
epilepsy thus reducing their workload. Many outstanding studies have given good results in …
A recent investigation on detection and classification of epileptic seizure techniques using EEG signal
The benefits of early detection and classification of epileptic seizures in analysis, monitoring
and diagnosis for the realization and actualization of computer-aided devices and recent …
and diagnosis for the realization and actualization of computer-aided devices and recent …
CNN based framework for detection of epileptic seizures
Epilepsy is a common neurological disease that uses electroencephalogram (EEG) data for
its detection purpose. Neurologists make the diagnosis by visual inspection of EEG reports …
its detection purpose. Neurologists make the diagnosis by visual inspection of EEG reports …
Epileptic-net: an improved epileptic seizure detection system using dense convolutional block with attention network from EEG
Epilepsy is a complex neurological condition that affects a large number of people
worldwide. Electroencephalography (EEG) measures the electrical activity of the brain and …
worldwide. Electroencephalography (EEG) measures the electrical activity of the brain and …
A hybrid deep learning approach for epileptic seizure detection in eeg signals
Early detection and proper treatment of epilepsy is essential and meaningful to those who
suffer from this disease. The adoption of deep learning (DL) techniques for automated …
suffer from this disease. The adoption of deep learning (DL) techniques for automated …
Deep-EEG: an optimized and robust framework and method for EEG-based diagnosis of epileptic seizure
Detecting brain disorders using deep learning methods has received much hype during the
last few years. Increased depth leads to more computational efficiency, accuracy, and …
last few years. Increased depth leads to more computational efficiency, accuracy, and …
Comparison of different input modalities and network structures for deep learning-based seizure detection
KO Cho, HJ Jang - Scientific reports, 2020 - nature.com
The manual review of an electroencephalogram (EEG) for seizure detection is a laborious
and error-prone process. Thus, automated seizure detection based on machine learning has …
and error-prone process. Thus, automated seizure detection based on machine learning has …
Epileptic eeg classification by using time-frequency images for deep learning
Epilepsy is one of the most common brain disorders worldwide. The most frequently used
clinical tool to detect epileptic events and monitor epilepsy patients is the EEG recordings …
clinical tool to detect epileptic events and monitor epilepsy patients is the EEG recordings …
Automatic seizure detection by convolutional neural networks with computational complexity analysis
Abstract Background and Objectives Nowadays, an automated computer-aided diagnosis
(CAD) is an approach that plays an important role in the detection of health issues. The main …
(CAD) is an approach that plays an important role in the detection of health issues. The main …