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

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

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 …

Abstract Background and Objective Brain tumor occurs because of anomalous development
of cells. It is one of the major reasons of death in adults around the globe. Millions of deaths …

Computer-aided detection/diagnosis (CAD) systems can enhance the diagnostic capabilities
of physicians and reduce the time required for accurate diagnosis. The objective of this …

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

We developed a novel computer-aided diagnosis (CAD) system that uses feature-ranking
and a genetic algorithm to analyze structural magnetic resonance imaging data; using this …

Abstract Machine learning algorithms and multivariate data analysis methods have been
widely utilized in the field of Alzheimer's disease (AD) research in recent years. Advances in …

Alzheimer's disease (AD) is a progressive, neurodegenerative brain disorder that attacks
neurotransmitters, brain cells, and nerves, affecting brain functions, memory, and behaviors …

Alzheimer's disease (AD) patients exhibit alterations in the functional connectivity between
spatially segregated brain regions which may be related to both local gray matter (GM) …