[HTML][HTML] Explainable deep-learning-based diagnosis of Alzheimer's disease using multimodal input fusion of PET and MRI Images

M Odusami, R Maskeliūnas, R Damaševičius… - Journal of Medical and …, 2023 - Springer
Purpose Alzheimer's disease (AD) is a progressive, incurable human brain illness that
impairs reasoning and retention as well as recall. Detecting AD in its preliminary stages …

Deep Learning-Assisted Diagnosis of Alzheimer's Disease from Brain Imaging Data

RR Yellu, Y Kukalakunta… - Journal of AI in Healthcare …, 2024 - healthsciencepub.com
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that primarily affects
older adults and is characterized by memory loss and cognitive decline. Early and accurate …

Multi-modal cross-attention network for Alzheimer's disease diagnosis with multi-modality data

J Zhang, X He, Y Liu, Q Cai, H Chen, L Qing - Computers in Biology and …, 2023 - Elsevier
Alzheimer's disease (AD) is a neurodegenerative disorder, the most common cause of
dementia, so the accurate diagnosis of AD and its prodromal stage mild cognitive …

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 …

Multi-modal data Alzheimer's disease detection based on 3D convolution

Z Kong, M Zhang, W Zhu, Y Yi, T Wang… - … Signal Processing and …, 2022 - Elsevier
Multi-modal medical imaging information has been widely used in computer-assisted
investigations and diagnoses. A typical example is that the combination of information from …

Multimodal fusion-based deep learning network for effective diagnosis of Alzheimer's disease

S Dwivedi, T Goel, M Tanveer, R Murugan… - IEEE …, 2022 - ieeexplore.ieee.org
Alzheimer's disease (AD) is a prevalent, irreversible, chronic, and degenerative disorder
whose diagnosis at the prodromal stage is critical. Mostly, single modality data, such as …

Diagnosis of Alzheimer's disease by joining dual attention CNN and MLP based on structural MRIs, clinical and genetic data

YR Qiang, SW Zhang, JN Li, Y Li, QY Zhou… - Artificial Intelligence in …, 2023 - Elsevier
Alzheimer's disease (AD) is an irreversible central nervous degenerative disease, while mild
cognitive impairment (MCI) is a precursor state of AD. Accurate early diagnosis of AD is …

A single model deep learning approach for Alzheimer's disease diagnosis

F Zhang, B Pan, P Shao, P Liu, S Shen, P Yao, RX Xu… - Neuroscience, 2022 - Elsevier
Early and accurate diagnosis of Alzheimer's disease (AD) and its prodromal period mild
cognitive impairment (MCI) is essential for the delayed disease progression and the …

[HTML][HTML] Multimodal and multiscale deep neural networks for the early diagnosis of Alzheimer's disease using structural MR and FDG-PET images

D Lu, K Popuri, GW Ding, R Balachandar, MF Beg - Scientific reports, 2018 - nature.com
Alzheimer's Disease (AD) is a progressive neurodegenerative disease where biomarkers for
disease based on pathophysiology may be able to provide objective measures for disease …

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 …