The network, with some or all characteristics of scale-free, self-similarity, self-organization,
attractor and small world, is defined as a complex network. The identification of significant …

Epilepsy is one of the most debilitating neurological diseases that abruptly alters a person's
way of life. Manual diagnosis is a laborious and time-consuming task prone to human error …

Automatic seizure prediction is crucial for developing a new therapy for patients suffering
from medically intractable epilepsy, possessing important clinical application value. In order …

Although recent studies have proposed seizure detection algorithms with good sensitivity
performance, there is a remained challenge that they were hard to achieve significantly short …

Epileptic seizure is one of the most common neurological disorders characterized by sudden
abnormal discharge of neurons in the brain. Automated seizure detection using …

Tailoring a deep convolutional neural network (DCNN) is a tedious and time-consuming task
in the field of medical image analysis. In this research paper, Deep-generative adversial …

Automatic seizure detection plays a key role in assisting clinicians for rapid diagnosis and
treatment of epilepsy. In view of the parallelism of temporal convolutional network (TCN) and …

This paper proposes an interpretable ensembled seizure detection procedure using
electroencephalography (EEG) data, which integrates data driven features and clinical …

Objective The objective is to implement a comprehensive Heuristic-CFCA (H-CFCA) a
feature classification system using Machine Learning and Deep Learning principles for …

One of the most severe neurological conditions that abruptly changes a person's way of life
is epileptic seizures. Recent diagnostic approaches have concentrated on creating …