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 …
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 …
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 …
Early diagnosis of mild cognitive impairment and Alzheimer's with event-related potentials and event-related desynchronization in N-back working memory tasks
Abstract Background and Objective: In this study we investigate whether or not event-related
potentials (ERP) and/or event-related (de) synchronization (ERD/ERS) can be used to …
potentials (ERP) and/or event-related (de) synchronization (ERD/ERS) can be used to …
Regularized linear discriminant analysis of EEG features in dementia patients
E Neto, F Biessmann, H Aurlien, H Nordby… - Frontiers in aging …, 2016 - frontiersin.org
The present study explores if EEG spectral parameters can discriminate between healthy
elderly controls (HC), Alzheimer's disease (AD) and vascular dementia (VaD) using. We …
elderly controls (HC), Alzheimer's disease (AD) and vascular dementia (VaD) using. We …
Diagnose Alzheimer's disease and mild cognitive impairment using deep CascadeNet and handcrafted features from EEG signals
K Rezaee, M Zhu - Biomedical Signal Processing and Control, 2025 - Elsevier
Alzheimer's disease (AD) is the most prevalent clinically diagnosed neurodegenerative
disorder. Early detection of mild cognitive impairment (MCI) is crucial for implementing …
disorder. Early detection of mild cognitive impairment (MCI) is crucial for implementing …
EEG-based clinical decision support system for Alzheimer's disorders diagnosis using EMD and deep learning techniques
Introduction Despite the existence of numerous clinical techniques for identifying
neurological brain disorders in their early stages, Electroencephalogram (EEG) data shows …
neurological brain disorders in their early stages, Electroencephalogram (EEG) data shows …
The effects of automated artifact removal algorithms on electroencephalography-based Alzheimer's disease diagnosis
Over the last decade, electroencephalography (EEG) has emerged as a reliable tool for the
diagnosis of cortical disorders such as Alzheimer's disease (AD). EEG signals, however, are …
diagnosis of cortical disorders such as Alzheimer's disease (AD). EEG signals, however, are …
Spinal cord stimulation modulates frontal delta and gamma in patients of minimally consciousness state
Spinal cord stimulation (SCS) has been suggested as a therapeutic technique for treating
patients with disorder of consciousness (DOC). Although studies have reported its benefits …
patients with disorder of consciousness (DOC). Although studies have reported its benefits …
Comparative analysis of weka-based classification algorithms on medical diagnosis datasets
Y Dou, W Meng - Technology and Health Care, 2023 - content.iospress.com
BACKGROUND: With the advent of 5G and the era of Big Data, the rapid development of
medical information technology around the world, the massive application of electronic …
medical information technology around the world, the massive application of electronic …