Multimodal fusion model for diagnosing mild cognitive impairment in unilateral middle cerebral artery steno-occlusive disease.

ABSTRACT:

Objectives

To propose a multimodal functional brain network (FBN) and structural brain network (SBN) topological feature fusion technique based on resting-state functional magnetic resonance imaging (rs-fMRI), diffusion tensor imaging (DTI), 3D-T1-weighted imaging (3D-T1WI), and demographic characteristics to diagnose mild cognitive impairment (MCI) in patients with unilateral middle cerebral artery (MCA) steno-occlusive disease.

Methods

The performances of different algorithms on the MCI dataset were evaluated using 5-fold cross-validation. The diagnostic results of the multimodal performance were evaluated using t-distributed stochastic neighbor embedding (t-SNE) analysis. The four-modal analysis method proposed in this study was applied to identify brain regions and conne

SUBMITTER: Yuan Z 

PROVIDER: S-EPMC11861546 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature