Systematic review on resting‐state EEG for Alzheimer's disease diagnosis and progression assessment
Alzheimer's disease (AD) is a neurodegenerative disorder that accounts for nearly 70% of
the more than 46 million dementia cases estimated worldwide. Although there is no cure for …
the more than 46 million dementia cases estimated worldwide. Although there is no cure for …
Measures of resting state EEG rhythms for clinical trials in Alzheimer's disease: recommendations of an expert panel
Abstract The Electrophysiology Professional Interest Area (EPIA) and Global Brain
Consortium endorsed recommendations on candidate electroencephalography (EEG) …
Consortium endorsed recommendations on candidate electroencephalography (EEG) …
EEG signal processing for Alzheimer's disorders using discrete wavelet transform and machine learning approaches
The most common neurological brain issue is Alzheimer's disease, which can be diagnosed
using a variety of clinical methods. However, the electroencephalogram (EEG) is shown to …
using a variety of clinical methods. However, the electroencephalogram (EEG) is shown to …
Predicting age from brain EEG signals—a machine learning approach
Objective: The brain age gap estimate (BrainAGE) is the difference between the estimated
age and the individual chronological age. BrainAGE was studied primarily using MRI …
age and the individual chronological age. BrainAGE was studied primarily using MRI …
An attention-based deep learning approach for the classification of subjective cognitive decline and mild cognitive impairment using resting-state EEG
Objective. This study aims to design and implement the first deep learning (DL) model to
classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state …
classify subjects in the prodromic states of Alzheimer's disease (AD) based on resting-state …
Spatial–temporal graph convolutional network for Alzheimer classification based on brain functional connectivity imaging of electroencephalogram
Functional connectivity of the human brain, representing statistical dependence of
information flow between cortical regions, significantly contributes to the study of the intrinsic …
information flow between cortical regions, significantly contributes to the study of the intrinsic …
[HTML][HTML] A comparison of resting state EEG and structural MRI for classifying Alzheimer's disease and mild cognitive impairment
Alzheimer's disease (AD) is the leading cause of dementia, accounting for 70% of cases
worldwide. By 2050, dementia prevalence will have tripled, with most new cases occurring …
worldwide. By 2050, dementia prevalence will have tripled, with most new cases occurring …
Machine learning algorithms and statistical approaches for Alzheimer's disease analysis based on resting-state EEG recordings: A systematic review
Alzheimer's Disease (AD) is a neurodegenerative disorder and the most common type of
dementia with a great prevalence in western countries. The diagnosis of AD and its …
dementia with a great prevalence in western countries. The diagnosis of AD and its …
Improving the healthcare effectiveness: The possible role of EHR, IoMT and blockchain
New types of patient health records aim to help physicians shift from a medical practice,
often based on their personal experience, towards one of evidence based medicine, thus …
often based on their personal experience, towards one of evidence based medicine, thus …
[Retracted] On Improved 3D‐CNN‐Based Binary and Multiclass Classification of Alzheimer's Disease Using Neuroimaging Modalities and Data Augmentation …
Alzheimer's disease (AD) is an irreversible illness of the brain impacting the functional and
daily activities of elderly population worldwide. Neuroimaging sensory systems such as …
daily activities of elderly population worldwide. Neuroimaging sensory systems such as …