Linking Data for Ontology Based Advising in Healthcare

Along with the massive influence of computational technologies in medical research and practice, the wide generation of patient, clinical and lab tests data make the assistance of intelligent information systems very important for correct therapy, surveillance and advising of the patient. Medical data is highly heterogeneous and with different structure and formats. Principal tasks of the work are focused at intelligent integration of all data related to a particular patient. Aside with the methodological aspects of linking medical data, an important part of the discussed study focuses on the design and development of a special purpose decision support system. This system enriches a specific ontology for diabetes mellitus with a set of newly defined rules, supporting the development of broad and more precise personalized dietary recommendations as a part of digitized healthcare assistance.