Convolutional neural network models of structural MRI for discriminating categories of cognitive impairment: a systematic review and meta-analysis.

ABSTRACT:

Background

Alzheimer's disease (AD) and mild cognitive impairment (MCI) pose significant challenges to public health and underscore the need for accurate and early diagnostic tools. Structural magnetic resonance imaging (sMRI) combined with advanced analytical techniques like convolutional neural networks (CNNs) seemed to offer a promising avenue for the diagnosis of these conditions. This systematic review and meta-analysis aimed to evaluate the diagnostic performance of CNN algorithms applied to sMRI data in differentiating between AD, MCI, and normal cognition (NC).

Methods

Following the PRISMA-DTA guidelines, a comprehensive literature search was carried out in PubMed and Web of Science databases for studies published between 2018 and 2024. Studies were included if they

SUBMITTER: Dong X 

PROVIDER: S-EPMC12482330 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature