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 …
Deep learning-based Alzheimer disease detection
SS Kundaram, KC Pathak - … of the Fourth International Conference on …, 2021 - Springer
Deep learning methods have gained more popularity recently in medical image analysis.
This work proposes a deep convolutional neural network (DCNN) for Alzheimer's disease …
This work proposes a deep convolutional neural network (DCNN) for Alzheimer's disease …
Two-stage deep learning model for Alzheimer's disease detection and prediction of the mild cognitive impairment time
Alzheimer's disease (AD) is an irreversible neurodegenerative disease characterized by
thinking, behavioral and memory impairments. Early prediction of conversion from mild …
thinking, behavioral and memory impairments. Early prediction of conversion from mild …
A deep feature-based real-time system for Alzheimer disease stage detection
The origin of dementia can be largely attributed to Alzheimer's disease (AD). The
progressive nature of AD causes the brain cell deterioration that eventfully leads to physical …
progressive nature of AD causes the brain cell deterioration that eventfully leads to physical …
Exploring deep transfer learning techniques for Alzheimer's dementia detection
Examination of speech datasets for detecting dementia, collected via various speech tasks,
has revealed links between speech and cognitive abilities. However, the speech dataset …
has revealed links between speech and cognitive abilities. However, the speech dataset …
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] Alzheimer's disease stage identification using deep learning models
Objective The aim of this research is to identify the stage of Alzheimer's Disease (AD)
patients through the use of mobility data and deep learning models. This process facilitates …
patients through the use of mobility data and deep learning models. This process facilitates …
A deep learning framework with an embedded-based feature selection approach for the early detection of the Alzheimer's disease
N Mahendran, DRV PM - Computers in Biology and Medicine, 2022 - Elsevier
Ageing is associated with various ailments including Alzheimer's disease (AD), which is a
progressive form of dementia. AD symptoms develop over a period of years and …
progressive form of dementia. AD symptoms develop over a period of years and …
Early diagnosis of Alzheimer's disease based on deep learning: A systematic review
Background The improvement of health indicators and life expectancy, especially in
developed countries, has led to population growth and increased age-related diseases …
developed countries, has led to population growth and increased age-related diseases …
Multimodal multitask deep learning model for Alzheimer's disease progression detection based on time series data
Early prediction of Alzheimer's disease (AD) is crucial for delaying its progression. As a
chronic disease, ignoring the temporal dimension of AD data affects the performance of a …
chronic disease, ignoring the temporal dimension of AD data affects the performance of a …