[HTML][HTML] Artificial intelligence in healthcare: review and prediction case studies

G Rong, A Mendez, EB Assi, B Zhao, M Sawan - Engineering, 2020‏ - Elsevier
Artificial intelligence (AI) has been develo** rapidly in recent years in terms of software
algorithms, hardware implementation, and applications in a vast number of areas. In this …

[Retracted] EEG‐Based Epileptic Seizure Detection via Machine/Deep Learning Approaches: A Systematic Review

I Ahmad, X Wang, M Zhu, C Wang, Y Pi… - Computational …, 2022‏ - Wiley Online Library
Epileptic seizure is one of the most chronic neurological diseases that instantaneously
disrupts the lifestyle of affected individuals. Toward develo** novel and efficient …

[HTML][HTML] Epileptic seizures detection using deep learning techniques: a review

A Shoeibi, M Khodatars, N Ghassemi, M Jafari… - International journal of …, 2021‏ - mdpi.com
A variety of screening approaches have been proposed to diagnose epileptic seizures,
using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities …

Efficient epileptic seizure prediction based on deep learning

H Daoud, MA Bayoumi - IEEE transactions on biomedical …, 2019‏ - ieeexplore.ieee.org
Epilepsy is one of the world's most common neurological diseases. Early prediction of the
incoming seizures has a great influence on epileptic patients' life. In this paper, a novel …

Convolutional neural networks for seizure prediction using intracranial and scalp electroencephalogram

ND Truong, AD Nguyen, L Kuhlmann, MR Bonyadi… - Neural Networks, 2018‏ - Elsevier
Seizure prediction has attracted growing attention as one of the most challenging predictive
data analysis efforts to improve the life of patients with drug-resistant epilepsy and tonic …

A review of feature extraction and performance evaluation in epileptic seizure detection using EEG

P Boonyakitanont, A Lek-Uthai, K Chomtho… - … Signal Processing and …, 2020‏ - Elsevier
Since the manual detection of electrographic seizures in continuous electroencephalogram
(EEG) monitoring is very time-consuming and requires a trained expert, attempts to develop …

A difference attention ResNet-LSTM network for epileptic seizure detection using EEG signal

X Qiu, F Yan, H Liu - Biomedical Signal Processing and Control, 2023‏ - Elsevier
Epileptic seizures can affect the patient's physical function and cause irreversible damage to
their brain. It is vital to detect epilepsy seizures in time and give patients antiepileptic …

D2PAM: Epileptic seizures prediction using adversarial deep dual patch attention mechanism

AA Khan, RK Madendran… - CAAI Transactions …, 2023‏ - Wiley Online Library
Epilepsy is considered as a serious brain disorder in which patients frequently experience
seizures. The seizures are defined as the unexpected electrical changes in brain neural …

EEG datasets for seizure detection and prediction—A review

S Wong, A Simmons, J Rivera‐Villicana… - Epilepsia …, 2023‏ - Wiley Online Library
Electroencephalogram (EEG) datasets from epilepsy patients have been used to develop
seizure detection and prediction algorithms using machine learning (ML) techniques with …

Two-layer LSTM network-based prediction of epileptic seizures using EEG spectral features

K Singh, J Malhotra - Complex & Intelligent Systems, 2022‏ - Springer
Epilepsy is a chronic nervous disorder, which disturbs the normal daily routine of an
epileptic patient due to sudden seizure onset. In this era of smart healthcare, automated …