[HTML][HTML] Neuroimaging modalities in Alzheimer's disease: diagnosis and clinical features
Alzheimer's disease (AD) is a neurodegenerative disease causing progressive cognitive
decline until eventual death. AD affects millions of individuals worldwide in the absence of …
decline until eventual death. AD affects millions of individuals worldwide in the absence of …
Impact of eeg parameters detecting dementia diseases: A systematic review
LM Sánchez-Reyes, J Rodríguez-Reséndiz… - IEEE …, 2021 - ieeexplore.ieee.org
Dementia diseases are increasing rapidly, according to the World Health Organization
(WHO), becoming an alarming problem for the health sector. The electroencephalogram …
(WHO), becoming an alarming problem for the health sector. The electroencephalogram …
Early detection of Alzheimer's disease from EEG signals using Hjorth parameters
Background Alzheimer's disease (AD) is a progressive neurodegenerative disorder of the
brain that ultimately results in the death of neurons and dementia. The prevalence of the …
brain that ultimately results in the death of neurons and dementia. The prevalence of the …
[HTML][HTML] Alzheimer's disease and frontotemporal dementia: A robust classification method of EEG signals and a comparison of validation methods
Dementia is the clinical syndrome characterized by progressive loss of cognitive and
emotional abilities to a degree severe enough to interfere with daily functioning. Alzheimer's …
emotional abilities to a degree severe enough to interfere with daily functioning. Alzheimer's …
DICE-net: a novel convolution-transformer architecture for Alzheimer detection in EEG signals
Objective: Alzheimer's disease (AD) is a progressive neurodegenerative disorder that affects
a significant percentage of the elderly. EEG has emerged as a promising tool for the timely …
a significant percentage of the elderly. EEG has emerged as a promising tool for the timely …
A novel electroencephalography based approach for Alzheimer's disease and mild cognitive impairment detection
B Oltu, MF Akşahin, S Kibaroğlu - Biomedical Signal Processing and …, 2021 - Elsevier
Background and objective Alzheimer's disease (AD) is characterized by cognitive,
behavioral and intellectual deficits. The term mild cognitive impairment (MCI) is used to …
behavioral and intellectual deficits. The term mild cognitive impairment (MCI) is used to …
Identification of Alzheimer's disease from central lobe EEG signals utilizing machine learning and residual neural network
IA Fouad, FEZM Labib - Biomedical Signal Processing and Control, 2023 - Elsevier
Cognitive and behavioral deficits are some of the symptoms of Alzheimer's disease, a
neurological disease caused by brain deterioration. Early diagnosis of the disease …
neurological disease caused by brain deterioration. Early diagnosis of the disease …
EEG based classification of children with learning disabilities using shallow and deep neural network
NPG Seshadri, S Agrawal, BK Singh… - … Signal Processing and …, 2023 - Elsevier
Learning disability (LD), a neurodevelopmental disorder that has severely impacted the lives
of many children all over the world. LD refers to significant deficiency in children's reading …
of many children all over the world. LD refers to significant deficiency in children's reading …
A systematic review and methodological analysis of EEG-based biomarkers of Alzheimer's disease
Alzheimer's disease (AD) is one of the most prevalent neurodegenerative disorders in the
world. Although there is no known cure for it at the present, preventive drug trials and …
world. Although there is no known cure for it at the present, preventive drug trials and …
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 …