Machine learning and deep learning approaches for brain disease diagnosis: principles and recent advances

P Khan, MF Kader, SMR Islam, AB Rahman… - Ieee …, 2021 - ieeexplore.ieee.org
Brain is the controlling center of our body. With the advent of time, newer and newer brain
diseases are being discovered. Thus, because of the variability of brain diseases, existing …

An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: Methods, challenges, and future works

A Shoeibi, P Moridian, M Khodatars… - Computers in biology …, 2022 - Elsevier
Epilepsy is a disorder of the brain denoted by frequent seizures. The symptoms of seizure
include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand …

[HTML][HTML] Multimodal detection of epilepsy with deep neural networks

L Ilias, D Askounis, J Psarras - Expert Systems with Applications, 2023 - Elsevier
Epilepsy constitutes a chronic noncommunicable disease of the brain affecting
approximately 50 million people around the world. Most of the existing research initiatives …

Hybrid attention network for epileptic EEG classification

Y Zhao, J He, F Zhu, T Xiao, Y Zhang… - … Journal of Neural …, 2023 - World Scientific
Automatic seizure detection from electroencephalography (EEG) based on deep learning
has been significantly improved. However, existing works have not adequately excavate the …

Evaluation of feature selection methods for classification of epileptic seizure EEG signals

SE Sánchez-Hernández, RA Salido-Ruiz… - Sensors, 2022 - mdpi.com
Epilepsy is a disease that decreases the quality of life of patients; it is also among the most
common neurological diseases. Several studies have approached the classification and …

Machine learning algorithms for epilepsy detection based on published EEG databases: A systematic review

A Miltiadous, KD Tzimourta, N Giannakeas… - IEEE …, 2022 - ieeexplore.ieee.org
Epilepsy is the only neurological condition for which electroencephalography (EEG) is the
primary diagnostic and important prognostic clinical tool. However, the manual inspection of …

Automatic seizure identification from EEG signals based on brain connectivity learning

Y Zhao, M Xue, C Dong, J He, D Chu… - … journal of neural …, 2022 - World Scientific
Epilepsy is a neurological disorder caused by brain dysfunction, which could cause
uncontrolled behavior, loss of consciousness and other hazards. Electroencephalography …

Self-supervised Learning with Attention Mechanism for EEG-based seizure detection

T Xiao, Z Wang, Y Zhang, S Wang, H Feng… - … Signal Processing and …, 2024 - Elsevier
Epilepsy is a neurological disorder caused by abnormal brain discharges, which can be
diagnosed by electroencephalography (EEG). Although EEG signals are usually easy to …

A hypergraph based Kohonen map for detecting intrusions over cyber–physical systems traffic

SS Jagtap, SS VS, V Subramaniyaswamy - Future Generation Computer …, 2021 - Elsevier
Abstract Cyber–Physical System acts as a cornerstone in Industry 4.0 by integrating
information-technology, electrical, and mechanical engineering under the same crown. This …

Phase space reconstruction, geometric filtering based Fisher discriminant analysis and minimum distance to the Riemannian means algorithm for epileptic seizure …

X Zhou, BWK Ling, Y Zhou, NF Law - Expert Systems with Applications, 2023 - Elsevier
Background Most clinicians observe the changes of the electroencephalograms (EEGs) via
the visual inspection of the recorded signals of the patients. However, the visual inspection …