A novel computational analysis integrating social determinants information from EHR and literature with Alzheimer's disease biological knowledge through large language models and knowledge graphs.

ABSTRACT:

Background and objectives

Alzheimer's disease (AD) and AD-related dementias (ADRD) are expected to affect over 100 million people by 2050, placing a significant strain on public health systems. Social determinants of health (SDoH), which include factors such as socioeconomic conditions and environment, play a crucial role in AD risk. Despite growing evidence, the understanding of SDoH's impact on AD remains limited.

Research design and methods

This study leverages large language models and knowledge graphs (KGs) to extract AD-related SDoH knowledge from literature and electronic health records (EHR). We integrate this knowledge into biological research on AD through KG construction and graph deep learning, performing KG-link predictions validated by multimodal biological dat

SUBMITTER: Shang T 

PROVIDER: S-EPMC12742847 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature