A probabilistic ontology-based platform for self-learning context-aware healthcare applications Femke Ongenae a,∗ , Maxim Claeys a , Thomas Dupont a , Wannes Kerckhove a , Piet Verhoeve b , Tom Dhaene a , Filip De Turck a a Department of Information Technology (INTEC), Ghent University - iMinds, Gaston Crommenlaan 8 bus 201, B-9050 Ghent, Belgium b iMinds VZW, Gaston Crommenlaan 8 bus 102, B-9050 Ghent, Belgium Abstract Context-aware platforms consist of dynamic algorithms that take the context information into account to adapt the behavior of the applications. The relevant context information is modeled in a context model. Recently, a trend has emerged towards capturing the context in an ontology, which formally models the concepts within a certain domain, their relations and properties. Although much research has been done on the subject, the adoption of context-aware services in healthcare is lagging behind what could be ex- pected. The main complaint made by users is that they had to significantly alter workflow patterns to accommodate the system. When new technology is introduced, the behavior of the users changes to adapt to it. Moreover, small differences in user requirements often occur between different environments where the application is deployed. However, it is difficult to foresee these * Corresponding author: Tel.: +32 9 331 49 38, Fax: +32 9 331 48 99 Email addresses: Femke.Ongenae@intec.UGent.be (Femke Ongenae), Maxim.Claeys@intec.UGent.be (Maxim Claeys), Thomas.Dupont@intec.UGent.be (Thomas Dupont), Wannes.Kerckhove@intec.UGent.be (Wannes Kerckhove), Piet.Verhoeve@iminds.be (Piet Verhoeve), Tom.Dhaene@intec.UGent.be (Tom Dhaene), Filip.DeTurck@intec.UGent.be (Filip De Turck) Preprint submitted to Expert Systems with Applications September 12, 2013