RT Journal Article
T1 An Extended Semantic Interoperability Model for Distributed Electronic Health Record Based on Fuzzy Ontology Semantics
A1 Adel, Ebtsam
A1 El-Sappagh, Shaker
A1 Barakat, Sherif
A1 Hu, Jong Wan
A1 Elmogy, Mohammed
K1 Semantic
K1 Electronic health record (EHR)
K1 Fuzzy ontology
K1 SPARQL
AB Semantic interoperability of distributed electronic health record (EHR) systems is a crucial problem for querying EHR and machine learning projects. The main contribution of this paper is to propose and implement a fuzzy ontology-based semantic interoperability framework for distributed EHR systems. First, a separate standard ontology is created for each input source. Second, a unified ontology is created that merges the previously created ontologies. However, this crisp ontology is not able to answer vague or uncertain queries. We thirdly extend the integrated crisp ontology into a fuzzy ontology by using a standard methodology and fuzzy logic to handle this limitation. The used dataset includes identified data of 100 patients. The resulting fuzzy ontology includes 27 class, 58 properties, 43 fuzzy data types, 451 instances, 8376 axioms, 5232 logical axioms, 1216 declarative axioms, 113 annotation axioms, and 3204 data property assertions. The resulting ontology is tested using real data from the MIMIC-III intensive care unit dataset and real archetypes from openEHR. This fuzzy ontology-based system helps physicians accurately query any required data about patients from distributed locations using near-natural language queries. Domain specialists validated the accuracy and correctness of the obtained results
PB MDPI
YR 2021
FD 2021
LK http://hdl.handle.net/10347/26652
UL http://hdl.handle.net/10347/26652
LA eng
NO Electronics 2021, 10(14), 1733; https://doi.org/10.3390/electronics10141733
NO This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2021R1A2B5B02002599)
DS Minerva
RD 8 jun 2026