A combination of dynamic community structure and machine learning methods in tracking Alzheimer's disease-related functional reorganization

Brain networks have a modular structure in function and this modular organization changes dynamically with time. However, the available brain network modularization methods are limited to detect functional modules for static brain network.So the aim of this sttudy is to propose a consensus algorithm to evaluate the modularization of functional brain network of healthy individuals and patients with Alzheimer's disease.The measures for the modularization of functional brain networks included normalized mutual information (NMI), average participation coefficient and classification accuracy.To evaluate the results from the consensus algorithm, machine learning based classification was performed on a new AD data sets.