An efficient ensemble approach for Alzheimer's disease detection using an adaptive synthetic technique and deep learning
Alzheimer's disease is an incurable neurological disorder that leads to a gradual decline in
cognitive abilities, but early detection can significantly mitigate symptoms. The automatic …
cognitive abilities, but early detection can significantly mitigate symptoms. The automatic …
[HTML][HTML] Ensemble learning using traditional machine learning and deep neural network for diagnosis of Alzheimer's disease
In recent years, Alzheimer's disease (AD) diagnosis using neuroimaging and deep learning
has drawn great research attention. However, due to the scarcity of training neuroimaging …
has drawn great research attention. However, due to the scarcity of training neuroimaging …
A robust and clinically applicable deep learning model for early detection of Alzheimer's
Alzheimer's disease, often known as dementia, is a severe neurodegenerative disorder that
causes irreversible memory loss by destroying brain cells. People die because there is no …
causes irreversible memory loss by destroying brain cells. People die because there is no …
Brain MRI analysis for Alzheimer's disease diagnosis using an ensemble system of deep convolutional neural networks
Alzheimer's disease is an incurable, progressive neurological brain disorder. Earlier
detection of Alzheimer's disease can help with proper treatment and prevent brain tissue …
detection of Alzheimer's disease can help with proper treatment and prevent brain tissue …
Robust hybrid deep learning models for Alzheimer's progression detection
The prevalence of Alzheimer's disease (AD) in the growing elderly population makes
accurately predicting AD progression crucial. Due to AD's complex etiology and …
accurately predicting AD progression crucial. Due to AD's complex etiology and …
Exploring deep transfer learning ensemble for improved diagnosis and classification of alzheimer's disease
Alzheimer's disease (AD) is a progressive and irreversible neurological disorder that affects
millions of people worldwide. Early detection and accurate diagnosis of AD are crucial for …
millions of people worldwide. Early detection and accurate diagnosis of AD are crucial for …
An ensemble of deep convolutional neural networks for Alzheimer's disease detection and classification
Alzheimer's Disease destroys brain cells causing people to lose their memory, mental
functions and ability to continue daily activities. It is a severe neurological brain disorder …
functions and ability to continue daily activities. It is a severe neurological brain disorder …
Ensembles of patch-based classifiers for diagnosis of Alzheimer diseases
There is ongoing research for the automatic diagnosis of Alzheimer's disease (AD) based on
traditional machine learning techniques, and deep learning-based approaches are …
traditional machine learning techniques, and deep learning-based approaches are …
Integrating convolutional neural networks, kNN, and Bayesian optimization for efficient diagnosis of Alzheimer's disease in magnetic resonance images
S Lahmiri - Biomedical Signal Processing and Control, 2023 - Elsevier
Deep learning is attracting growing interest from biomedical engineering community.
Researchers and clinicians are also increasingly interested in development of machine …
Researchers and clinicians are also increasingly interested in development of machine …
Dad-net: Classification of alzheimer's disease using adasyn oversampling technique and optimized neural network
Alzheimer's Disease (AD) is a neurological brain disorder that causes dementia and
neurological dysfunction, affecting memory, behavior, and cognition. Deep Learning (DL), a …
neurological dysfunction, affecting memory, behavior, and cognition. Deep Learning (DL), a …