An Ontology-driven Adaptive System for the Patient Treatment Management

Emna Mezghani, Marcos Da Silveira, Cédric Pruski, Ernesto Exposito, Khalil Drira
2016 Proceedings of the 28th International Conference on Software Engineering and Knowledge Engineering  
Advances in the Web and healthcare data capture technologies have far-reaching benefits for the development of new clinical decision support systems that accelerate decisionmaking and generate personalized treatments. However, the diversity of healthcare data formats, the lack of computer interpretable representation of medical interventions, and the distribution of reliable medical knowledge sources constitute important barriers to better support the medical decision process. To deal with
more » ... issues, we propose the Treatment Plan Ontology (TPO) that formalizes medical interventions, and allows medical systems sharing and reasoning over them. This knowledge together with the acquired patient data are then reused by the autonomic processes that we have developed in order to timely detect anomalies and support the physicians in personalizing the patient treatment at the right time. We demonstrate the system efficiency through a use case for managing hyperglycemia in type 2 diabetes.
doi:10.18293/seke2016-155 dblp:conf/seke/MezghaniSPED16 fatcat:qgpprioh3jgjhelwhdpede7vzq