Despite its great promise, neuroimaging has yet to substantially impact clinical practice and
public health. However, a develo** synergy between emerging analysis techniques and …

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 …

In this chapter, we explore Support Vector Machine (SVM)—a machine learning method that
has become exceedingly popular for neuroimaging analysis in recent years. Because of …

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 …

Some forms of mild cognitive impairment (MCI) are the clinical precursors of Alzheimer's
disease (AD), while other MCI types tend to remain stable over-time and do not progress to …

Many neurological diseases and delineating pathological regions have been analyzed, and
the anatomical structure of the brain researched with the aid of magnetic resonance imaging …

Alzheimer's Disease (AD) is a progressive neurodegenerative disease where biomarkers for
disease based on pathophysiology may be able to provide objective measures for disease …

Multimodal medical imaging plays a pivotal role in clinical diagnosis and research, as it
combines information from various imaging modalities to provide a more comprehensive …

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 …

Mild cognitive impairment (MCI) is a transitional stage between age-related cognitive
decline and Alzheimer's disease (AD). For the effective treatment of AD, it would be …