A review of methods of diagnosis and complexity analysis of Alzheimer's disease using EEG signals

M Ouchani, S Gharibzadeh… - BioMed Research …, 2021 - Wiley Online Library
This study will concentrate on recent research on EEG signals for Alzheimer's diagnosis,
identifying and comparing key steps of EEG‐based Alzheimer's disease (AD) detection …

A computerized analysis with machine learning techniques for the diagnosis of Parkinson's disease: past studies and future perspectives

A Rana, A Dumka, R Singh, MK Panda, N Priyadarshi - Diagnostics, 2022 - mdpi.com
According to the World Health Organization (WHO), Parkinson's disease (PD) is a
neurodegenerative disease of the brain that causes motor symptoms including slower …

Deep learning-based classification of healthy aging controls, mild cognitive impairment and Alzheimer's disease using fusion of MRI-PET imaging

VPS Rallabandi, K Seetharaman - Biomedical Signal Processing and …, 2023 - Elsevier
Automated detection of dementia stage using multimodal imaging modalities will be helpful
for improving the clinical diagnosis. In this study, we develop the Inception-ResNet wrapper …

RETRACTED ARTICLE: Deep learning and image processing-based early detection of Alzheimer disease in cognitively normal individuals: Deep learning and image …

P Borkar, VA Wankhede, DT Mane, S Limkar… - Soft Computing, 2024 - dl.acm.org
RETRACTED ARTICLE: Deep learning and image processing-based early detection of
Alzheimer disease in cognitively normal individuals: Deep learning and image processing-based …

Pareto optimized adaptive learning with transposed convolution for image fusion Alzheimer's disease classification

M Odusami, R Maskeliūnas, R Damaševičius - Brain sciences, 2023 - mdpi.com
Alzheimer's disease (AD) is a neurological condition that gradually weakens the brain and
impairs cognition and memory. Multimodal imaging techniques have become increasingly …

Effects of transcranial magnetic stimulation on neurobiological changes in Alzheimer's disease

S Bashir, M Uzair, T Abualait… - Molecular …, 2022 - spandidos-publications.com
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by cognitive
decline and brain neuronal loss. A pioneering field of research in AD is brain stimulation via …

Hybrid D-OCapNet: Automated Multi-Class Alzheimer's Disease Classification in Brain MRI Using Hybrid Dense Optimal Capsule Network.

AV Nisha, MP Rajasekaran… - … Journal of Pattern …, 2023 - search.ebscohost.com
Efficient detection of Alzheimer's disease (AD) is challenging in medical image processing.
Different methodologies are proposed for detecting AD at earlier stages, but certain demerits …

An efficient multi class Alzheimer detection using hybrid equilibrium optimizer with capsule auto encoder

NP Ansingkar, RB Patil, PD Deshmukh - Multimedia Tools and …, 2022 - Springer
Alzheimer is an advanced nervous brain disease. In old aged people, Alzheimer is also
causing the death. The earlier prediction of Alzheimer's disease (AD) helps to proper …

Multimodal magnetic resonance imaging for Alzheimer's disease diagnosis using hybrid features extraction and ensemble support vector machines

L Houria, N Belkhamsa, A Cherfa… - International Journal of …, 2023 - Wiley Online Library
Magnetic resonance imaging (MRI) is increasingly used in the diagnosis of Alzheimer's
disease (AD) in order to identify abnormalities in the brain. Indeed, cortical atrophy, a …

Hemispheric cortical, cerebellar and caudate atrophy associated to cognitive impairment in Metropolitan Mexico City young adults exposed to fine particulate matter …

L Calderón-Garcidueñas, J Hernández-Luna… - Toxics, 2022 - mdpi.com
Exposures to fine particulate matter PM2. 5 are associated with Alzheimer's, Parkinson's
(AD, PD) and TDP-43 pathology in young Metropolitan Mexico City (MMC) residents. High …