Multiview Incomplete Knowledge Graph Integration with application to cross-institutional EHR data harmonization

202232 citationsJournal Articlehybrid Open Access

Authors

Doudou Zhou · University of California, Davis

Gan Zi-ming · University of Illinois Chicago

Xu Shi · University of Michigan

Alina Patwari · Boston Latin Academy

Everett Rush · Oak Ridge National Laboratory

Clara-Lea Bonzel · Harvard University

Vidul Ayakulangara Panickan ·

Abstract

The proposed MIKGI algorithm can effectively integrate incomplete summary data from biomedical text and EHR data to generate harmonized embeddings for EHR codes for knowledge graph modeling and cross-institutional translation of EHR codes.

Topics & Keywords

Biomedical Text Mining and Ontologies Machine Learning in Healthcare Topic Modeling

UN Sustainable Development Goals

Partnerships for the goals

Publication Details

Published in: Journal of Biomedical Informatics

Volume 133, pp. 104147-104147

DOI: 10.1016/j.jbi.2022.104147

Field-Weighted Citation Impact: 2.51