… prediction of the incoming seizures has a great influence on epileptic patients’ life. In this
paper, a novel patient-specific seizure prediction technique based on deep learn… deep learning …

… We propose a deep learning based method for the prediction of epileptic seizures. Our
proposed method consists of the preprocessing of EEG signals, comprehensive feature extraction …

… Moghim and Corne [49], in this study, illustrated an algorithm used for epilepsy prediction,
called ASPPR (advance seizure prediction via preictal relabeling). It helps the understanding …

… In this paper, an efficient seizure prediction method is proposed using raw EEG data. A
deep learning technique is used for important feature extraction from EEG data for the …

… We present a proof-of-concept for a seizure prediction system that … deep learning and the
TrueNorth processor can be leveraged to advance the task of patient-specific seizure prediction…

… In this paper, we propose a seizure prediction method using deep learning methods. Section
II discusses the state of the art seizure prediction methods using scalp EEG data, Section III …

… seizure prediction. In Section III, we explain the dataset used for the study and deep learning
… In Section IV, we present the results of proposed deep learning models, and we also …

… We propose a seizure prediction system for real-time big data analysis of EEG that can be
… III-B, a deep learning technique is developed using Stack Autoencoder for unsupervised …

… seizure prediction. In Section III, we explain the dataset used for the study and deep learning
… In Section IV, we present the results of proposed deep learning models, and we also …

… We described an end-to-end CNN architecture for seizure prediction in this paper. Instead
of using more commonly seen features from the frequency domain, raw EEG signals are used …