SemanticCT: A Semantically-Enabled System for Clinical Trials

Abstract. In this paper, we propose an approach of semantically en-abled systems for clinical trials. The goals are not only to achieve the interoperability by semantic integration of heterogeneous data in clini-cal trials, but also to facilitate automatic reasoning and data processing services for decision support systems in various settings of clinical trials. We have implemented the proposed approach in a system called Se-manticCT. SemanticCT is built on the top of LarKC (Large Knowledge Collider), a platform for scalable semantic data processing. SemanticCT has been integrated with large-scale trial data and patient data, and provided various automatic services for clinical trials, which include au-tomatic patient recruitment service (i.e., identifying eligible patients for a trial) and trial finding service (i.e., finding suitable trials for a patient).