Alzheimer's Disease (AD) is the most prevalent and rapidly progressing neurodegenerative
disorder among the elderly and is a leading cause of dementia. AD results in significant …

Central nervous system (CNS) disorders and diseases are expected to rise sharply in the
coming years, partly because of the world's aging population. Medicines for the treatment of …

Abstract Alzheimer's disease (AD), the most prevalent form of dementia, requires early
prediction for timely intervention. Current deep learning approaches, particularly those using …

As a deep learning method, graph convolution network (GCN) has the advantage of dealing
with non-Euclidean domain problems and is constantly applied in the research of computer …

Alzheimer's disease (AD) is the most prevalent form of dementia, with no current cure. Early
screening and intervention are vital. In multimodal AD data, besides neuroimaging …

The neuroscience community has developed many convolutional neural networks (CNNs)
for the early detection of Alzheimer's disease (AD). Population graphs are thought of as non …

Artificial intelligence (AI) and machine learning (ML) approaches are increasingly being
used in dementia research. However, several methodological challenges exist that may limit …

Alzheimer's disease (AD) is a progressive neurodegenerative disorder with an impairment of
cognition and memory. Current research on connectomics have now related changes in the …

Abstract Alzheimer's disease (AD), one of the most common dementias, has about 4.6
million new cases yearly worldwide. Due to the significant amount of suspected AD patients …

Alzheimer's disease (AD), the most prevalent degenerative brain disease associated with
dementia, requires early diagnosis to alleviate worsening of symptoms through appropriate …