Deep learning for motor imagery EEG-based classification: A review
Objectives The availability of large and varied Electroencephalogram (EEG) datasets,
rapidly advances and inventions in deep learning techniques, and highly powerful and …
rapidly advances and inventions in deep learning techniques, and highly powerful and …
Machine learning and deep learning approaches for brain disease diagnosis: principles and recent advances
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 …
diseases are being discovered. Thus, because of the variability of brain diseases, existing …
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 …
Reviewing methods of deep learning for diagnosing COVID-19, its variants and synergistic medicine combinations
Q Rafique, A Rehman, MS Afghan, HM Ahmad… - Computers in Biology …, 2023 - Elsevier
The COVID-19 pandemic has necessitated the development of reliable diagnostic methods
for accurately detecting the novel coronavirus and its variants. Deep learning (DL) …
for accurately detecting the novel coronavirus and its variants. Deep learning (DL) …
Diagnosis and prognosis of mental disorders by means of EEG and deep learning: a systematic mapping study
Electroencephalography (EEG) is used in the diagnosis and prognosis of mental disorders
because it provides brain biomarkers. However, only highly trained doctors can interpret …
because it provides brain biomarkers. However, only highly trained doctors can interpret …
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 …
Computational Intelligence and Metaheuristic Techniques for Brain Tumor Detection through IoMT‐Enabled MRI Devices
The brain tumor is the 22nd most common cancer worldwide, with 1.8% of new cancers. It is
likely the most severe ailment that necessitates early discovery and treatment, and it …
likely the most severe ailment that necessitates early discovery and treatment, and it …
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 …
common neurological diseases. Several studies have approached the classification and …
Improving multi-class motor imagery EEG classification using overlapping sliding window and deep learning model
Motor imagery (MI) electroencephalography (EEG) signals are widely used in BCI systems.
MI tasks are performed by imagining doing a specific task and classifying MI through EEG …
MI tasks are performed by imagining doing a specific task and classifying MI through EEG …
CNN based framework for detection of epileptic seizures
Epilepsy is a common neurological disease that uses electroencephalogram (EEG) data for
its detection purpose. Neurologists make the diagnosis by visual inspection of EEG reports …
its detection purpose. Neurologists make the diagnosis by visual inspection of EEG reports …