ARCH: Large-scale knowledge graph via aggregated narrative codified health records analysis.

ABSTRACT:

Objective

Electronic health record (EHR) systems contain a wealth of clinical data stored as both codified data and free-text narrative notes (NLP). The complexity of EHR presents challenges in feature representation, information extraction, and uncertainty quantification. To address these challenges, we proposed an efficient Aggregated naRrative Codified Health (ARCH) records analysis to generate a large-scale knowledge graph (KG) for a comprehensive set of EHR codified and narrative features.

Methods

Using data from 12.5 million Veterans Affairs patients, ARCH first derives embedding vectors and generates similarities along with associated p-values to measure the strength of relatedness between clinical features with statistical certainty quantification. Next, ARCH perform

SUBMITTER: Gan Z 

PROVIDER: S-EPMC12066163 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature