Similarity estimation among OWL descriptions of computational cardiology problems in a knowledge base

The purpose of this study is to evaluate ontologies in order to achieve an efficient search of medical computational problems in cardiology (MCP). These ontologies provide the ability to standardize the description process of cardiology problems and algorithms by utilizing Ontology Web Language -Description Logic (OWL-DL). The final aim is to build a knowledge base (KB) from the OWL descriptions of the MCPs. The identification of a new cardiology problem or related to this problem included in KB is proposed to be conducted by cosine-based similarity. A novel algorithm that constructs the MCPs vectors from the ontology individuals is presented. These vectors are defined by a matrix based on problems, Concept Unique Identifier (CUI) Keywords and CUI Categories. The CUIs are automatically received by the Unified Medical Language System Knowledge Server (UMLS-KS) and stored into ontologies. Finally, an example where twelve cardiology problems vectors are constructed from the corresponding individuals of the ontology classes is presented and analyzed