Epilepsy disease is one of the most prevalent neurological disorders caused by malfunction
of large symptoms number of neurons. That's lead us to propose an automated approach to …

In this paper, the efficiently extracted and reduced features using deep long short-term
memory (DLSTM) of the epileptic EEG signal integrated with minimum variance kernel …

Objective. Significant progress has been witnessed in within-subject seizure detection from
electroencephalography (EEG) signals. Consequently, more and more works have been …

Epilepsy is a neurological disorder that affects the normal functioning of the brain. More than
10% of the population across the globe is affected by this disorder. Electroencephalogram …

In the diagnosis of epileptic seizures, classification is an important step that directly affects
the results. Visual inspection of Electroencephalogram (EEG) is a relatively common analytic …

Deep learning architectures have brought about new heights in computer vision, with the
most common approach being the Convolutional Neural Network (CNN). Through CNN …

Epilepsy is one of the most common neurological disorders, affecting 50 million people
worldwide. Despite the availability of numerous anti-epileptic drugs, it is often impossible to …

Epilepsy affects millions worldwide, making timely seizure detection crucial for effective
treatment and enhanced well-being. Electroencephalogram (EEG) analysis offers a non …

Epileptic seizure is a chronic and non-communicable disease which occurs in people of all
ages. In the detection of epileptic seizures, electroencephalography (EEG) plays a vital role …

Neurological disorders are identified using brain scans obtained via modalities such as
electroencephalogram (EEG), magnetic resonance imaging (MRI), computed tomography …