Alzheimer's disease (AD) is a neurological illness that causes cognitive impairment and has
no known treatment. The premise for delivering timely therapy is the early diagnosis of AD …

Methods for the analysis of neuroimaging data have advanced significantly since the
beginning of neuroscience as a scientific discipline. Today, sophisticated statistical …

Artificial intelligence (AI)-based diagnostic systems provide less error-prone and safer
support to clinicians, enhancing the medical decision-making process. This study presents a …

The most commonly used neuroimaging biomarkers of brain structure, particularly in
neurodegenerative diseases, have traditionally been summary measurements from ROIs …

Abstract Background and Objective The importance of early diagnosis of Alzheimer's
Disease (AD) is by no means negligible because no cure has been recognized for it rather …

Deep learning has been widely investigated in brain image computational analysis for
diagnosing brain diseases such as Alzheimer's disease (AD). Most of the existing methods …

Memory loss and aberrant neuronal network activity are part of the earliest hallmarks of
Alzheimer's disease (AD). Electroacupuncture (EA) has been recognized as a cognitive …

Convolutional neural networks (CNNs) have been widely used in medical imaging
applications, including brain diseases such as Alzheimer's disease (AD) classification based …

Longitudinal hippocampal atrophy is commonly used as progressive marker assisting
clinical diagnose of dementia. However, precise quantification of the atrophy is limited by …

Objective We aimed to use the onset time of Alzheimer's disease (AD) as the reference time
to longitudinally investigate the atrophic characteristics of brain structures prior to the onset …