Enhancing Automated Decision Support across Medical and Oral Health   Domains with Semantic Web Technologies
  Research has shown that the general health and oral health of an individual are closely related. Accordingly, current practice of isolating the information base of medical and oral health domains can be dangerous and detrimental to the health of the individual. However, technical issues such as heterogeneous data collection and storage formats, limited sharing of patient information and lack of decision support over the shared information are the principal reasons for the current state of affairs. To address these issues, the following research investigates the development and application of a cross-domain ontology and rules to build an evidence-based and reusable knowledge base consisting of the inter-dependent conditions from the two domains. Through example implementation of the knowledge base in Protege, we demonstrate the effectiveness of our approach in reasoning over and providing decision support for cross-domain patient information. 
Tejal Shah, Fethi Rabhi, Pradeep Ray and Kerry Taylor
cs.AI cs.IR