Building a Biomedical Ontology for Respiratory Tract Infection

Respiratory tract infections are most common disease which can affect any human during any part of their age. According to sources almost 60% of all antibiotic prescription is due to Respiratory tract infection. The concepts and their relations related to Respiratory tract infection are need to be explained with the help of biomedical literature as well as historical records. But these literature or records cannot be efficiently managed by users due to their unstructured representation. Biomedical Ontologies are best way to identify the concepts and their respective relations from huge amount of unstructured data. Our research aimed to create a biomedical Ontology for the domain of Respiratory tract infection using UMLS as a data source, which contains concepts, subtypes, their relationships, and semantic types. As a result ontology contains 26 main and sub types of Respiratory tract infections, also 234 broad relations with 107325 relation counts and 1151 narrow relation with 34580 relation counts. The ontology created is evaluated by domain experts and results are formulated.