Application of ontology in medical heterogeneous data integration

Abstract

In the process of data integration, medical data is a huge obstacle to the development of medical information because of its complicated data type, large amount of data and semantic heterogeneity among different data sources. Integration of massive medical heterogeneous data is the urgent need to promote the process of medical information to be solved. According to the characteristics of medical data sources, an ontology-based medical heterogeneous data integration scheme is proposed. By introducing the medical similarity algorithm into the hybrid medical ontology, not only the multi-semantic problem is solved, but also the current heterogeneity of mass medical data is eliminated. Finally, experiments show that this method performs well in eliminating the semantic uncertainty of data in the medical field and can improve the integration efficiency of heterogeneous data in the medical data warehouse. It is practically feasible to solve the problem of medical heterogeneous data integration.