Deep-learning-based diagnosis and prognosis of Alzheimer's disease: A comprehensive review
Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most
common cause of Dementia. Neuroimaging analyses, such as T1 weighted magnetic …
common cause of Dementia. Neuroimaging analyses, such as T1 weighted magnetic …
Machine learning with multimodal neuroimaging data to classify stages of Alzheimer's disease: A systematic review and meta-analysis
In recent years, Alzheimer's disease (AD) has been a serious threat to human health.
Researchers and clinicians alike encounter a significant obstacle when trying to accurately …
Researchers and clinicians alike encounter a significant obstacle when trying to accurately …
A deep learning approach for robust, multi-oriented, and curved text detection
Automatic text localization and segmentation in a normal environment with vertical or curved
texts are core elements of numerous tasks comprising the identification of vehicles and self …
texts are core elements of numerous tasks comprising the identification of vehicles and self …
Pixel-level fusion approach with vision transformer for early detection of Alzheimer's disease
Alzheimer's disease (AD) has become a serious hazard to human health in recent years,
and proper screening and diagnosis of AD remain a challenge. Multimodal neuroimaging …
and proper screening and diagnosis of AD remain a challenge. Multimodal neuroimaging …
[HTML][HTML] Review of multimodal machine learning approaches in healthcare
Abstract Machine learning methods in healthcare have traditionally focused on using data
from a single modality, limiting their ability to effectively replicate the clinical practice of …
from a single modality, limiting their ability to effectively replicate the clinical practice of …
A robust deep learning framework based on spectrograms for heart sound classification
Heart sound analysis plays an important role in early detecting heart disease. However,
manual detection requires doctors with extensive clinical experience, which increases …
manual detection requires doctors with extensive clinical experience, which increases …
Multimodal neuroimaging based Alzheimer's disease diagnosis using evolutionary RVFL classifier
Alzheimer's disease (AD) is one of the most known causes of dementia which can be
characterized by continuous deterioration in the cognitive skills of elderly people. It is a non …
characterized by continuous deterioration in the cognitive skills of elderly people. It is a non …
A systematic literature review on the significance of deep learning and machine learning in predicting Alzheimer's disease
Background Alzheimer's disease (AD) is the most prevalent cause of dementia,
characterized by a steady decline in mental, behavioral, and social abilities and impairs a …
characterized by a steady decline in mental, behavioral, and social abilities and impairs a …
Pareto optimized adaptive learning with transposed convolution for image fusion Alzheimer's disease classification
Alzheimer's disease (AD) is a neurological condition that gradually weakens the brain and
impairs cognition and memory. Multimodal imaging techniques have become increasingly …
impairs cognition and memory. Multimodal imaging techniques have become increasingly …
Automatic early diagnosis of Alzheimer's disease using 3D deep ensemble approach
Alzheimer's disease (AD) is considered the 6 leading cause of death worldwide. Early
diagnosis of AD is not an easy task, and no preventive cures have been discovered yet …
diagnosis of AD is not an easy task, and no preventive cures have been discovered yet …