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 …
include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand …
An overview of machine learning methods in enabling IoMT-based epileptic seizure detection
ALN Al-Hajjar, AKM Al-Qurabat - The Journal of Supercomputing, 2023 - Springer
The healthcare industry is rapidly automating, in large part because of the Internet of Things
(IoT). The sector of the IoT devoted to medical research is sometimes called the Internet of …
(IoT). The sector of the IoT devoted to medical research is sometimes called the Internet of …
Blood pressure detection using CNN-LSTM model
Blood pressure (BP) is a key indication that needs to be checked on a regular basis. For
maintaining a healthy life normal blood pressure is essential, and a continuous change can …
maintaining a healthy life normal blood pressure is essential, and a continuous change can …
A convolutional neural network approach for diabetic retinopathy classification
Diabetic Retinopathy (DR) is a kind of problem which affects diabetic patients, particularly
those at their age of working, and can result in vision impairment and possibly irreversible …
those at their age of working, and can result in vision impairment and possibly irreversible …
Liver disease prediction using machine learning classification techniques
Machine Learning is a process which is used to discover patterns in huge data/large data
set to enable decision, thereby allowing machines to go through a learning process (ie …
set to enable decision, thereby allowing machines to go through a learning process (ie …
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 …
their brain. It is vital to detect epilepsy seizures in time and give patients antiepileptic …
Automated Seizure Detection using Theta Band
The EEG signal is made up of numerous frequency bands that characterize human
behaviours like emotion, attentiveness, and sleep status, among others. In order to detect …
behaviours like emotion, attentiveness, and sleep status, among others. In order to detect …
A LSTM-CNN Model for Epileptic Seizures Detection using EEG Signal
Neurologists visually inspect electroencephalogram (EEG) reports to get the epilepsy
diagnosis. Scholars have suggested automated techniques to detect the ailment due to the …
diagnosis. Scholars have suggested automated techniques to detect the ailment due to the …
Epileptic seizures detection in EEG signals using fusion handcrafted and deep learning features
Epilepsy is a brain disorder disease that affects people's quality of life.
Electroencephalography (EEG) signals are used to diagnose epileptic seizures. This paper …
Electroencephalography (EEG) signals are used to diagnose epileptic seizures. This paper …
The applied principles of EEG analysis methods in neuroscience and clinical neurology
H Zhang, QQ Zhou, H Chen, XQ Hu, WG Li, Y Bai… - Military Medical …, 2023 - Springer
Electroencephalography (EEG) is a non-invasive measurement method for brain activity.
Due to its safety, high resolution, and hypersensitivity to dynamic changes in brain neural …
Due to its safety, high resolution, and hypersensitivity to dynamic changes in brain neural …