abstract Multimodal fusion of different types of neural image data provides an irreplaceable
opportunity to take advantages of complementary cross-modal information that may only …

Background Graph theory and machine learning have been shown to be effective ways of
classifying different stages of Alzheimer's disease (AD). Most previous studies have only …

Alzheimer's disease (AD) is one of the most serious neurological disorders for elderly
people. AD affected patient experiences severe memory loss. One of the main reasons for …

Clinical studies have shown that female brains are more predisposed to neurodegenerative
diseases such as Alzheimer's disease (AD), but the cellular and molecular mechanisms …

Background Alzheimer's disease (AD) is the most common age-related problem and
progresses in different stages, including mild cognitive impairment (early stage), mild …

Alzheimer's disease (AD) is the most common neurodegenerative disorder worldwide.
Mitochondrial dysfunction is thought to be an early event in the onset and progression of AD; …

A number of studies have indicated alterations of brain morphology in individuals with
autism spectrum disorder (ASD); however, how ASD influences the topological organization …

Background: Changes in the metabolic and structural brain networks in mild cognitive
impairment (MCI) have been widely researched. However, few studies have compared the …

Network analysis provides a rich framework to model complex phenomena, such as human
brain connectivity. It has proven efficient to understand their natural properties and design …

The resting-state functional magnetic resonance imaging (rs-fMRI) modality has gained
widespread acceptance as a promising method for analyzing a variety of neurological and …