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 …

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 …

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 …

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 …

Standard univariate analysis of neuroimaging data has revealed a host of neuroanatomical
and functional differences between healthy individuals and patients suffering a wide range …

Background The aim of this study is to use classification methods to predict future onset of
Alzheimer's disease in cognitively normal subjects through automated linguistic analysis …

The multivariate analysis of brain signals has recently sparked a great amount of interest, yet
accessible and versatile tools to carry out decoding analyses are scarce. Here we introduce …

Importance Machine learning algorithms could be used as the basis for clinical decision-
making aids to enhance clinical practice. Objective To assess the ability of machine learning …

Abstract The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing,
longitudinal, multicenter study designed to develop clinical, imaging, genetic, and …