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 …
Identifying underlying patterns in Alzheimer's disease trajectory: a deep learning approach and Mendelian randomization analysis
Background Alzheimer's disease (AD) is a heterogeneously progressive neurodegeneration
disorder with varied rates of deterioration, either between subjects or within different stages …
disorder with varied rates of deterioration, either between subjects or within different stages …
Alzheimer's disease detection and stage identification from magnetic resonance brain images using vision transformer
MH Alshayeji - Machine Learning: Science and Technology, 2024 - iopscience.iop.org
Abstract Machine learning techniques applied in neuroimaging have prompted researchers
to build models for early diagnosis of brain illnesses such as Alzheimer's disease (AD) …
to build models for early diagnosis of brain illnesses such as Alzheimer's disease (AD) …
A novel approach to enhance feature selection using linearity assessment with ordinary least squares regression for Alzheimer's Disease stage classification
B Mabrouk, N Bouattour, N Mabrouki, L Sellami… - Multimedia Tools and …, 2024 - Springer
Diagnosing Alzheimer's disease (AD) in its prodromal stage is a significantly crucial area of
research. Approximately 50% of individuals within the well-known Mild Cognitive Impairment …
research. Approximately 50% of individuals within the well-known Mild Cognitive Impairment …
Efficient surface crack segmentation for industrial and civil applications based on an enhanced YOLOv8 model
Crack segmentation is essential for preventive maintenance in various civil and industrial
applications. It makes it possible to identify and divide structural cracks or defects …
applications. It makes it possible to identify and divide structural cracks or defects …
Early Alzheimer? s disease diagnosis using an XG-Boost model applied to MRI images
Abstract Introduction: Early Alzheimer's disease (AD) diagnosis is critical to improving the
success of new treatments in clinical trials, especially at the early mild cognitive impairment …
success of new treatments in clinical trials, especially at the early mild cognitive impairment …
Diagnosis of brain disease based on the deep learning algorithms of neural imaging techniques
Q Wang - Journal of Intelligent & Fuzzy Systems, 2024 - content.iospress.com
Neuroimaging technology is considered a non-invasive method research the structure and
function of the brain which have been widely used in neuroscience, psychiatry, psychology …
function of the brain which have been widely used in neuroscience, psychiatry, psychology …
Implementasi Deep Learning dalam Pendeteksian Dini Penyakit Alzhaimer
I Mulyana, BA Sekti - Prosiding SISFOTEK, 2024 - seminar.iaii.or.id
Abstract Alzheimer's Disease (AD), is a neurodegenerative condition that develops slowly
and generally occurs in older people. The aim of this research is to optimize Deep Learning …
and generally occurs in older people. The aim of this research is to optimize Deep Learning …