Semi-automated ontology development and management system applied to medically unexplained syndromes in the U.S. veterans population

Abstract

Terminologies or ontologies to describe patient-reported information are lacking. The development and maintenance of ontologies is usually a manual, lengthy, and resource-intensive process. To support the development of medical specialty-specific ontologies, we created a semi-automated ontology development and management system (SEAM). SEAM supports ontology development by automatically extracting terms, concepts, and relations from narrative text, and then offering a streamlined graphical user interface to edit and create content in the ontology and finally export it in OWL format. The graphical user interface implements card sorting for synonym grouping and concept laddering for hierarchy construction. We used SEAM to create ontologies to support medically unexplained syndromes detection and management among veterans in the U.S.