Alzheimer's disease (AD) presents a significant challenge in neurodegenerative research
and clinical practice due to its complex etiology and progressive nature. The integration of …

Alzheimer's disease (AD) is a neurodegenerative disorder that affects millions of people
worldwide, making early detection essential for effective intervention. This review paper …

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 …

Alzheimer's disease (AD) is a degenerative neurological disorder with incurable
characteristics. To identify the substantial solution, we used a structural biomarker (structural …

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) …

Alzheimer's disease (AD) is a neurological condition that causes significant cognitive
deterioration within the brain. Early detection can lead to an early diagnosis of the illness …

Background: Early identification of Alzheimer's disease (AD) is essential for optimal
treatment and management. Deep learning (DL) technologies, including convolutional …

Introduction Machine learning (ML) algorithms and statistical modeling offer a potential
solution to offset the challenge of diagnosing early Alzheimer's disease (AD) by leveraging …

In brain-related diseases, including Brain Tumours and Alzheimer's, accurate and timely
diagnosis is crucial for effective medical intervention. Current state-of-the-art (SOTA) …

Alzheimer's disease (AD) imposes a growing burden on public health due to its impact on
memory, cognition, behavior, and social skills. Early detection using non-invasive brain …