A deep learning framework for identifying Alzheimer's disease using fMRI-based brain network.

ABSTRACT:

Background

The convolutional neural network (CNN) is a mainstream deep learning (DL) algorithm, and it has gained great fame in solving problems from clinical examination and diagnosis, such as Alzheimer's disease (AD). AD is a degenerative disease difficult to clinical diagnosis due to its unclear underlying pathological mechanism. Previous studies have primarily focused on investigating structural abnormalities in the brain's functional networks related to the AD or proposing different deep learning approaches for AD classification.

Objective

The aim of this study is to leverage the advantages of combining brain topological features extracted from functional network exploration and deep features extracted by the CNN. We establish a novel fMRI-based classification framework

SUBMITTER: Wang R 

PROVIDER: S-EPMC10442560 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature