Advanced brain imaging for the diagnosis of Alzheimer disease
Brain imaging techniques using PET improve our understanding of the different AD-related
pathologies and their relationship with each other along the course of disease. With more …
pathologies and their relationship with each other along the course of disease. With more …
Ensemble deep learning for Alzheimer's disease characterization and estimation
Alzheimer's disease, which is characterized by a continual deterioration of cognitive abilities
in older people, is the most common form of dementia. Neuroimaging data, for example …
in older people, is the most common form of dementia. Neuroimaging data, for example …
Accurate detection of Alzheimer's disease using lightweight deep learning model on MRI data
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by cognitive
impairment and aberrant protein deposition in the brain. Therefore, the early detection of AD …
impairment and aberrant protein deposition in the brain. Therefore, the early detection of AD …
[HTML][HTML] Classification of Alzheimer's disease using MRI data based on Deep Learning Techniques
SE Sorour, AA Abd El-Mageed, KM Albarrak… - Journal of King Saud …, 2024 - Elsevier
Alzheimer's Disease (AD) is a worldwide concern impacting millions of people, with no
effective treatment known to date. Unlike cancer, which has seen improvement in preventing …
effective treatment known to date. Unlike cancer, which has seen improvement in preventing …
Wearable sensors for supporting diagnosis, prognosis, and monitoring of neurodegenerative diseases
The incidence of neurodegenerative disorders (NDs) is increasing in an aging population.
NDs encompass a wide range of disorders characterized by the progressive deterioration of …
NDs encompass a wide range of disorders characterized by the progressive deterioration of …
Computational Intelligence-Based Disease Severity Identification: A Review of Multidisciplinary Domains
Disease severity identification using computational intelligence-based approaches is
gaining popularity nowadays. Artificial intelligence and deep-learning-assisted approaches …
gaining popularity nowadays. Artificial intelligence and deep-learning-assisted approaches …
fMRI-Based Alzheimer's Disease Detection Using the SAS Method with Multi-Layer Perceptron Network
A Chelladurai, DL Narayan, PB Divakarachari… - Brain Sciences, 2023 - mdpi.com
In the present scenario, Alzheimer's Disease (AD) is one of the incurable neuro-
degenerative disorders, which accounts for nearly 60% to 70% of dementia cases. Currently …
degenerative disorders, which accounts for nearly 60% to 70% of dementia cases. Currently …
TEDformer: Temporal Feature Enhanced Decomposed Transformer for Long-term Series Forecasting
J Fan, B Wang, D Bian - IEEE Access, 2023 - ieeexplore.ieee.org
In recent years, Transformer-based models have achieved good results in the analysis and
application of time series. In particular, the introduction of Autoformer has further improved …
application of time series. In particular, the introduction of Autoformer has further improved …
Revolutionizing Alzheimer's Disease Prediction using InceptionV3 in Deep Learning
R Jansi, N Gowtham, S Ramachandran… - 2023 7th …, 2023 - ieeexplore.ieee.org
Since Alzheimer's disease is a neurological condition that affects millions of people
worldwide, early detection is vital for enabling successful treatment. Recent advances in …
worldwide, early detection is vital for enabling successful treatment. Recent advances in …
Automatic Classification of Alzheimer's Using Brain MRI Data and the ResNet152V2 Architecture
Alzheimer's disease is a neurological condition that typically affects elderly people and
causes memory loss and cognitive deterioration. Effective intervention and therapy for …
causes memory loss and cognitive deterioration. Effective intervention and therapy for …