[HTML][HTML] Medical big data: neurological diseases diagnosis through medical data analysis
Diagnosis of neurological diseases is a growing concern and one of the most difficult
challenges for modern medicine. According to the World Health Organisation's recent report …
challenges for modern medicine. According to the World Health Organisation's recent report …
[HTML][HTML] 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 …
[HTML][HTML] A spectrogram image based intelligent technique for automatic detection of autism spectrum disorder from EEG
Autism spectrum disorder (ASD) is a developmental disability characterized by persistent
impairments in social interaction, speech and nonverbal communication, and restricted or …
impairments in social interaction, speech and nonverbal communication, and restricted or …
[HTML][HTML] EEG signal analysis for diagnosing neurological disorders using discrete wavelet transform and intelligent techniques
Analysis of electroencephalogram (EEG) signals is essential because it is an efficient
method to diagnose neurological brain disorders. In this work, a single system is developed …
method to diagnose neurological brain disorders. In this work, a single system is developed …
Accurate detection of autism using Douglas-Peucker algorithm, sparse coding based feature mapping and convolutional neural network techniques with EEG signals
Abstract Autism Spectrum Disorders (ASD) is a collection of complicated neurological
disorders that first show in early childhood. Electroencephalogram (EEG) signals are widely …
disorders that first show in early childhood. Electroencephalogram (EEG) signals are widely …
Fractality and a wavelet-chaos-neural network methodology for EEG-based diagnosis of autistic spectrum disorder
A method is presented for investigation of EEG of children with autistic spectrum disorder
using complexity and chaos theory with the goal of discovering a nonlinear feature space …
using complexity and chaos theory with the goal of discovering a nonlinear feature space …
EEG‐based computer aided diagnosis of autism spectrum disorder using wavelet, entropy, and ANN
Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with core
impairments in the social relationships, communication, imagination, or flexibility of thought …
impairments in the social relationships, communication, imagination, or flexibility of thought …
Common spatial pattern technique with EEG signals for diagnosis of autism and epilepsy disorders
Electroencephalogram (EEG) signals reflect the activities or electrical disturbances in
neurons in the human brain. Therefore, these signals are vital for diagnosing certain brain …
neurons in the human brain. Therefore, these signals are vital for diagnosing certain brain …
[HTML][HTML] Automatic diagnosis of neurological diseases using MEG signals with a deep neural network
The application of deep learning to neuroimaging big data will help develop computer-aided
diagnosis of neurological diseases. Pattern recognition using deep learning can extract …
diagnosis of neurological diseases. Pattern recognition using deep learning can extract …
A dynamic filtering DF-RNN deep-learning-based approach for EEG-based neurological disorders diagnosis
G Bouallegue, R Djemal, SA Alshebeili… - IEEE …, 2020 - ieeexplore.ieee.org
Filtering of unwanted signals has a great impact on the performance of EEG signal
processing applied to neurological disorders diagnosis. It is so difficult to remove …
processing applied to neurological disorders diagnosis. It is so difficult to remove …