SemanticCT: A Semantically-Enabled System for Clinical Trials

  • Zhisheng Huang
  • Annette ten Teije
  • Frank van Harmelen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8268)


In this paper, we propose an approach of semantically enabled systems for clinical trials. The goals are not only to achieve the interoperability by semantic integration of heterogeneous data in clinical 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 SemanticCT. 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 automatic patient recruitment service (i.e., identifying eligible patients for a trial) and trial finding service (i.e., finding suitable trials for a patient).


Regular Expression Semantic Annotation Semantic Data SPARQL Query Semantic Search 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Zhisheng Huang
    • 1
  • Annette ten Teije
    • 1
  • Frank van Harmelen
    • 1
  1. 1.Department of Computer ScienceVU University AmsterdamThe Netherlands

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