A review of deep transfer learning approaches for class-wise prediction of Alzheimer's disease using MRI images
Alzheimer's disease is an irreversible, progressive neurodegenerative disorder that destroys
the brain and memory functionalities. In Alzheimer's disease, the brain starts shrinking, and …
the brain and memory functionalities. In Alzheimer's disease, the brain starts shrinking, and …
Artificial intelligence models in the diagnosis of adult-onset dementia disorders: A review
G Battineni, N Chintalapudi, MA Hossain, G Losco… - Bioengineering, 2022 - mdpi.com
Background: The progressive aging of populations, primarily in the industrialized western
world, is accompanied by the increased incidence of several non-transmittable diseases …
world, is accompanied by the increased incidence of several non-transmittable diseases …
Multi-modal brain tumor detection using deep neural network and multiclass SVM
Background and Objectives: Clinical diagnosis has become very significant in today's health
system. The most serious disease and the leading cause of mortality globally is brain cancer …
system. The most serious disease and the leading cause of mortality globally is brain cancer …
AlzheimerNet: An effective deep learning based proposition for alzheimer's disease stages classification from functional brain changes in magnetic resonance images
Alzheimer's disease is largely the underlying cause of dementia due to its progressive
neurodegenerative nature among the elderly. The disease can be divided into five stages …
neurodegenerative nature among the elderly. The disease can be divided into five stages …
[HTML][HTML] A deep learning based convolutional neural network model with VGG16 feature extractor for the detection of Alzheimer Disease using MRI scans
Alzheimer's disease (AD) is one of the most prevalent types of dementia, which primarily
affects people over age 60. In clinical practice, it is a challenging task to identify AD in its …
affects people over age 60. In clinical practice, it is a challenging task to identify AD in its …
Prediction of Cognitive decline in Parkinson's Disease using clinical and DAT SPECT Imaging features, and Hybrid Machine Learning systems
M Hosseinzadeh, A Gorji, A Fathi Jouzdani… - Diagnostics, 2023 - mdpi.com
Background: We aimed to predict Montreal Cognitive Assessment (MoCA) scores in
Parkinson's disease patients at year 4 using handcrafted radiomics (RF), deep (DF), and …
Parkinson's disease patients at year 4 using handcrafted radiomics (RF), deep (DF), and …
Quantifying the impact of Pyramid Squeeze Attention mechanism and filtering approaches on Alzheimer's disease classification
B Yan, Y Li, L Li, X Yang, T Li, G Yang… - Computers in Biology and …, 2022 - Elsevier
Brain medical imaging and deep learning are important foundations for diagnosing and
predicting Alzheimer's disease. In this study, we explored the impact of different image …
predicting Alzheimer's disease. In this study, we explored the impact of different image …
[HTML][HTML] Efficient self-attention mechanism and structural distilling model for Alzheimer's disease diagnosis
Structural magnetic resonance imaging (sMRI) is commonly used for the identification of
Alzheimer's disease because of its keen insight into atrophy-induced changes in brain …
Alzheimer's disease because of its keen insight into atrophy-induced changes in brain …
Explainable deep-learning-based diagnosis of Alzheimer's disease using multimodal input fusion of PET and MRI Images
Purpose Alzheimer's disease (AD) is a progressive, incurable human brain illness that
impairs reasoning and retention as well as recall. Detecting AD in its preliminary stages …
impairs reasoning and retention as well as recall. Detecting AD in its preliminary stages …
[HTML][HTML] Classification of Alzheimer's disease using MRI data based on Deep Learning Techniques
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 …