Semantics Driven Approach for Knowledge Acquisition From EMRs
Semantic computing technologies have matured to be applicable to many critical domains such as national security, life sciences, and health care. However, the key to their success is the availability of a rich domain knowledge base. The creation and refinement of domain knowledge bases pose difficult challenges. The existing knowledge bases in the health care domain are rich in taxonomic relationships, but they lack non-taxonomic (domain) relationships. In this paper, we describe a semiautomatic technique for enriching existing domain knowledge bases with causal relationships gleaned from Electronic Medical Records (EMR) data. We determine missing causal relationships between domain concepts by validating domain knowledge against EMR data sources and leveraging semantic-based techniques to derive plausible relationships that can rectify knowledge gaps. Our evaluation demonstrates that semantic techniques can be employed to improve the efficiency of knowledge acquisition.
Digital Object Identifier (DOI)
Published in IEEE Journal of Biomedical and Health Informatics, Volume 18, Issue 2, 2014, pages 515-524.
© IEEE, 2014
Perera, S., Henson, C. A., Thirunarayan, K., Sheth, A. P., & Nair, S. (2014). Semantics Driven Approach for Knowledge Acquisition From EMRs. IEEE Journal of Biomedical and Health Informatics, 18 (2), 515-524. https://doi.org/10.1109/jbhi.2013.2282125