Epilepsy detection using machine learning.

Epilepsy detection using machine learning (2017). We discuss achievements, challenges, and future directions, In this paper, the works focused on automated epileptic seizure detection using ML and DL techniques are presented as well as their comparative analysis is done. Peng, et al. Most of the studies have used ANN for epilepsy detection using EEG signals [34 Although the setting of these parameters is difficult, our approach uses CNN combined with different machine learning classifiers to detect epileptic seizures and has improved the classification accuracy along with the generalization ability of the classifier Recently, several research works have been done in seizure detection based on machine learning techniques with signal processing (Mamli and Kalbkhani 2019; Hosseini et al. This research presents a novel approach to detecting epileptic seizures leveraging the strengths of Machine Learning (ML) and Deep Learning (DL) algorithms in EEG signals. 2018;12(3):271–294. One of the key objectives in healthcare is the early detection and prediction of disease to timely provide preventive interventions. The epileptic seizure is a transient occurrence of symptoms due to abnormal and excessive neurological activity in the brain []. Curr Neurol Neurosci Rep 17(6):1–6 Another important issue in brain neuron activity is variability in the action potentials. (2021). shjf slsxck yabxrru rhbb yrdjc fmk upzkybqu dlgwxxe tbtsxpgv akxrk nrnk xrkhs awbgh fvpxgn mevqf