Neuroimaging has made it possible to measure pathological brain changes associated with
Alzheimer's disease (AD) in vivo. Over the past decade, these measures have been …

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

Recently, deep-learning-based approaches have been proposed for the classification of
neuroimaging data related to Alzheimer's disease (AD), and significant progress has been …

Alzheimer's disease is an incurable, progressive neurological brain disorder. Earlier
detection of Alzheimer's disease can help with proper treatment and prevent brain tissue …

Brain functional imaging data, especially functional magnetic resonance imaging (fMRI)
data, have been employed to reflect functional integration of the brain. Alteration in brain …

For the last decade, it has been shown that neuroimaging can be a potential tool for the
diagnosis of Alzheimer's Disease (AD) and its prodromal stage, Mild Cognitive Impairment …

Alzheimer's disease (AD) will become a global burden in the coming decades according to
the latest statistical survey. How to effectively detect AD or MCI (mild cognitive impairment) …

Recently, there have been great interests for computer-aided diagnosis of Alzheimer's
disease (AD) and its prodromal stage, mild cognitive impairment (MCI). Unlike the previous …

Abstract Machine learning techniques are increasingly being used in making relevant
predictions and inferences on individual subjects neuroimaging scan data. Previous studies …

In this article we review recent research on diffusion tensor imaging (DTI) of white matter
(WM) integrity and the implications for age-related differences in cognition. Neurobiological …