Development and validation of immune-based biomarkers and deep learning models for Alzheimer's disease.

ABSTRACT: Background: Alzheimer's disease (AD) is the most common form of dementia in old age and poses a severe threat to the health and life of the elderly. However, traditional diagnostic methods and the ATN diagnostic framework have limitations in clinical practice. Developing novel biomarkers and diagnostic models is necessary to complement existing diagnostic procedures. Methods: The AD expression profile dataset GSE63060 was downloaded from the NCBI GEO public database for preprocessing. AD-related differentially expressed genes were screened using a weighted co-expression network and differential expression analysis, and functional enrichment analysis was performed. Subsequently, we screened hub genes by random forest, analyzed the correlation between hub genes and immune cells

SUBMITTER: He Y 

PROVIDER: S-EPMC9441688 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature