We are happy to announce that we got a paper accepted for presentation at iiWAS2020 (Information Integration and Web-based Applications & Services). iiWAS2020 is a leading international conference for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all information integration and web-based applications & services related areas.
- Towards an On-tology Representing Characteristics of Inflammatory Bowel Disease
By Abderrahmane Khiat, Mirette Elias, Ann Christina Foldenauer, Michaela Koehm, Irina Blumenstein, and Giulio Napolitano.Abstract
Inflammatory bowel disease (IBD), including Crohn’s Disease (CD) and Ulcerative Colitis (UC), is a chronic disease characterized by numerous, hard to predict periods of relapse and remission. “Dig-ital twin” approaches, leveraging personalized predictive models, would significantly enhance therapeutic decision-making and cost-effectiveness. However, the associated computational and statistical methods require high quality data from a large population of patients. Such a comprehensive repository is very challenging to build, though, and none is available for IBD. To compensate the scarcity of data, a promising approach is to employ a knowledge graph, which is built from the available data and would help predicting IBD episodes and delivering more relevant personalized therapy at the lowest cost. In this research in progress, we present a knowledge graph developed on the basis of patient data collected in the University Hospital Frankfurt. First, we designed Chronisch-entzündliche Darmerkrankungen (CED) ontology that encompasses the vocabulary , specifications and characteristics associated by physicians with IBD patients, such as disease classification schemas (e.g. Montreal Classification of inflammatory bowel disease [17]), status of the disease activity, past and current medications. Next, we defined the mappings between ontology entities and database variables. Physicians participating in the Fraunhofer MED 2 ICIN project, together with the project members, validated the ontology and the knowledge graph. Furthermore, the knowledge graph has been validated against the competency questions compiled by physicians.