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 parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease
Some forms of mild cognitive impairment (MCI) are the clinical precursors of Alzheimer's
disease (AD), while other MCI types tend to remain stable over-time and do not progress to …
disease (AD), while other MCI types tend to remain stable over-time and do not progress to …
[HTML][HTML] Predicting Alzheimer's disease progression using multi-modal deep learning approach
Alzheimer's disease (AD) is a progressive neurodegenerative condition marked by a decline
in cognitive functions with no validated disease modifying treatment. It is critical for timely …
in cognitive functions with no validated disease modifying treatment. It is critical for timely …
[HTML][HTML] Hybridized deep learning approach for detecting Alzheimer's disease
Alzheimer's disease (AD) is mainly a neurodegenerative sickness. The primary
characteristics are neuronal atrophy, amyloid deposition, and cognitive, behavioral, and …
characteristics are neuronal atrophy, amyloid deposition, and cognitive, behavioral, and …
[HTML][HTML] Convolutional neural networks-based MRI image analysis for the Alzheimer's disease prediction from mild cognitive impairment
Mild cognitive impairment (MCI) is the prodromal stage of Alzheimer's disease (AD).
Identifying MCI subjects who are at high risk of converting to AD is crucial for effective …
Identifying MCI subjects who are at high risk of converting to AD is crucial for effective …
[HTML][HTML] AD-NET: Age-adjust neural network for improved MCI to AD conversion prediction
Abstract The prediction of Mild Cognitive Impairment (MCI) patients who are at higher risk
converting to Alzheimer's Disease (AD) is critical for effective intervention and patient …
converting to Alzheimer's Disease (AD) is critical for effective intervention and patient …
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 …
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 …
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 …
Transfer learning for predicting conversion from mild cognitive impairment to dementia of Alzheimer's type based on a three-dimensional convolutional neural network
Dementia of Alzheimer's type (DAT) is associated with devastating and irreversible cognitive
decline. Predicting which patients with mild cognitive impairment (MCI) will progress to DAT …
decline. Predicting which patients with mild cognitive impairment (MCI) will progress to DAT …