Multimodal neuroimaging based Alzheimer's disease diagnosis using evolutionary RVFL classifier

T Goel, R Sharma, M Tanveer… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Alzheimer's disease (AD) is one of the most known causes of dementia which can be
characterized by continuous deterioration in the cognitive skills of elderly people. It is a non …

Conv-ervfl: Convolutional neural network based ensemble RVFL classifier for Alzheimer's disease diagnosis

R Sharma, T Goel, M Tanveer… - IEEE Journal of …, 2022 - ieeexplore.ieee.org
As per the latest statistics, Alzheimer's disease (AD) has become a global burden over the
following decades. Identifying AD at the intermediate stage became challenging, with mild …

Multimodal MRI based classification and prediction of Alzheimer's disease using random forest ensemble

A Thushara, CUD Amma, A John… - … Technologies for High …, 2020 - ieeexplore.ieee.org
Alzheimer's disease (AD) is a neurodegenerative disorder that affects millions of people
worldwide and it accounts for a significant decrease in the quality of life of patients and their …

Ensemble of deep convolutional neural networks based multi‐modality images for Alzheimer's disease diagnosis

X Fang, Z Liu, M Xu - IET Image Processing, 2020 - Wiley Online Library
Alzheimer's disease (AD) is one of the most common progressive neurodegenerative
diseases. Structural magnetic resonance imaging (MRI) would provide abundant information …

[Retracted] Machine Learning and Image Processing Enabled Evolutionary Framework for Brain MRI Analysis for Alzheimer's Disease Detection

M Kamal, AR Pratap, M Naved… - Computational …, 2022 - Wiley Online Library
Alzheimer's disease is characterized by the presence of abnormal protein bundles in the
brain tissue, but experts are not yet sure what is causing the condition. To find a cure or …

[HTML][HTML] Alzheimer's disease diagnosis framework from incomplete multimodal data using convolutional neural networks

M Abdelaziz, T Wang, A Elazab - Journal of Biomedical Informatics, 2021 - Elsevier
Alzheimer's disease (AD) is a severe irreversible neurodegenerative disease that has great
sufferings on patients and eventually leads to death. Early detection of AD and its prodromal …

FAF-DRVFL: Fuzzy activation function based deep random vector functional links network for early diagnosis of Alzheimer disease

R Sharma, T Goel, M Tanveer, S Dwivedi… - Applied Soft …, 2021 - Elsevier
Alzheimer's disease (AD) is a degenerative neural condition marked by gradual memory
loss and cognitive impairment. It is irreversible in nature and leads to progressive cerebral …

A multilayered framework for diagnosis and classification of Alzheimer's disease using transfer learned Alexnet and LSTM

P Goyal, R Rani, K Singh - Neural Computing and Applications, 2024 - Springer
Alzheimer's disease (AD) is the most frequent type of dementia that has no effective cure,
except early discovery and treatment that may help patients to include successful years in …

Ensemble of ROI-based convolutional neural network classifiers for staging the Alzheimer disease spectrum from magnetic resonance imaging

S Ahmed, BC Kim, KH Lee, HY Jung… - PLoS …, 2020 - journals.plos.org
Patches from three orthogonal views of selected cerebral regions can be utilized to learn
convolutional neural network (CNN) models for staging the Alzheimer disease (AD) …

Deep learning and multimodal feature fusion for the aided diagnosis of Alzheimer's disease

H Jia, H Lao - Neural Computing and Applications, 2022 - Springer
The accurate diagnosis of Alzheimer's disease (AD) in the early stages, such as significant
memory concern (SMC) and mild cognitive impairment (MCI), is essential in order to slow its …