Deep learning for spatio-temporal data mining: A survey
With the fast development of various positioning techniques such as Global Position System
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …
(GPS), mobile devices and remote sensing, spatio-temporal data has become increasingly …
Deep learning to detect Alzheimer's disease from neuroimaging: A systematic literature review
Alzheimer's Disease (AD) is one of the leading causes of death in developed countries.
From a research point of view, impressive results have been reported using computer-aided …
From a research point of view, impressive results have been reported using computer-aided …
A deep learning approach for automated diagnosis and multi-class classification of Alzheimer's disease stages using resting-state fMRI and residual neural networks
Alzheimer's disease (AD) is an incurable neurodegenerative disorder accounting for 70%–
80% dementia cases worldwide. Although, research on AD has increased in recent years …
80% dementia cases worldwide. Although, research on AD has increased in recent years …
Deep learning based pipelines for Alzheimer's disease diagnosis: a comparative study and a novel deep-ensemble method
Background Alzheimer's disease is a chronic neurodegenerative disease that destroys brain
cells, causing irreversible degeneration of cognitive functions and dementia. Its causes are …
cells, causing irreversible degeneration of cognitive functions and dementia. Its causes are …
A 3D densely connected convolution neural network with connection-wise attention mechanism for Alzheimer's disease classification
J Zhang, B Zheng, A Gao, X Feng, D Liang… - Magnetic Resonance …, 2021 - Elsevier
Purpose Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative
disease. In recent years, machine learning methods have been widely used on analysis of …
disease. In recent years, machine learning methods have been widely used on analysis of …
Applications of deep learning to MRI images: A survey
Deep learning provides exciting solutions in many fields, such as image analysis, natural
language processing, and expert system, and is seen as a key method for various future …
language processing, and expert system, and is seen as a key method for various future …
A survey on deep learning-based non-invasive brain signals: recent advances and new frontiers
Brain signals refer to the biometric information collected from the human brain. The research
on brain signals aims to discover the underlying neurological or physical status of the …
on brain signals aims to discover the underlying neurological or physical status of the …
Deep convolution neural network based system for early diagnosis of Alzheimer's disease
Abstract Objectives Alzheimer's Disease (AD) is the most general type of dementia. In all
leading countries, it is one of the primary reasons of death in senior citizens. Currently, it is …
leading countries, it is one of the primary reasons of death in senior citizens. Currently, it is …
A new deep belief network-based multi-task learning for diagnosis of Alzheimer's disease
Accurate classification of Alzheimer's disease (AD) and mild cognitive impairment (MCI),
especially distinguishing the progressive MCI (pMCI) from stable MCI (sMCI), will be helpful …
especially distinguishing the progressive MCI (pMCI) from stable MCI (sMCI), will be helpful …
Multi-modal deep learning model for auxiliary diagnosis of Alzheimer's disease
F Zhang, Z Li, B Zhang, H Du, B Wang, X Zhang - Neurocomputing, 2019 - Elsevier
Alzheimer's disease (AD) is one of the most difficult to cure diseases. Alzheimer's disease
seriously affects the normal lives of the elderly and their families. The mild cognitive …
seriously affects the normal lives of the elderly and their families. The mild cognitive …