Alzheimer's disease is an incurable neurodegenerative disease primarily affecting the
elderly population. Efficient automated techniques are needed for early diagnosis of …

Neuroimaging-based single subject prediction of brain disorders has gained increasing
attention in recent years. Using a variety of neuroimaging modalities such as structural …

Deep neural networks have led to state-of-the-art results in many medical imaging tasks
including Alzheimer's disease (AD) detection based on structural magnetic resonance …

Computer Aided Diagnosis (CAD) constitutes an important tool for the early diagnosis of
Alzheimer's Disease (AD), which, in turn, allows the application of treatments that can be …

Abstract Introduction The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued
development and standardization of methodologies for biomarkers and has provided an …

Determination of sensitive and specific markers of very early AD progression is intended to
aid researchers and clinicians to develop new treatments and monitor their effectiveness, as …

Background Hippocampus is one of the first structures affected by neurodegenerative
diseases such as Alzheimer's disease (AD) and mild cognitive impairment (MCI) …

Many current statistical and machine learning methods have been used to explore
Alzheimer's disease (AD) and its associated patterns that contribute to the disease …

In recent years, Alzheimer's disease (AD) diagnosis using neuroimaging and deep learning
has drawn great research attention. However, due to the scarcity of training neuroimaging …

We propose a novel classification framework to precisely identify individuals with
Alzheimer's disease (AD) or mild cognitive impairment (MCI) from normal controls (NC). The …