An Extended Semantic Interoperability Model for Distributed Electronic Health Record Based on Fuzzy Ontology Semantics

Semantic interoperability of distributed electronic health record (EHR) systems is a crucial problem for querying EHR and machine learning projects. The main contribution this paper to propose implement fuzzy ontology-based semantic framework systems. First, separate standard ontology created each input source. Second, unified that merges the previously ontologies. However, crisp not able answer vague or uncertain queries. We thirdly extend integrated into by using methodology logic handle limitation. used dataset includes identified data 100 patients. resulting 27 class, 58 properties, 43 types, 451 instances, 8376 axioms, 5232 logical 1216 declarative 113 annotation 3204 property assertions. tested real from MIMIC-III intensive care unit archetypes openEHR. This system helps physicians accurately query any required about patients locations near-natural language Domain specialists validated accuracy correctness obtained results.