@inbook{d5c0fdc5d7844aac9a5be1ed8b03bdf6,
  title     = "Towards automatic patient eligibility assessment: from free-text criteria to queries",
  abstract  = "The presented work contributes to bridging the representation of clinical trials and patient data. Our ultimate goal is to support the trial recruitment, by automating the process of formalizing eligibility criteria of clinical trials, starting from free text of criteria and leading to a computable representation. This paper discusses the final step in the pipeline i.e. generating queries from the structured representation consisting of detected patterns and semantic entities. The queries allow to evaluate patient eligibility for a given trial. To enable easy incorporation of semantic reasoning using medical ontologies, we built the queries in SPARQL and use the OWL representation of one the standards for patient data storage - openEHR archetypes and NCI ontology. The available public repository of archetypes and the expressivity of SPARQL allow to create template queries for the majority of patterns. © 2013 Springer-Verlag.",
  author    = "K. Milian and {ten Teije}, A.C.M.",
  year      = "2013",
  doi       = "10.1007/978-3-642-38326-7_12",
  isbn      = "9783642383250",
  pages     = "78--83",
  editor    = "N. Peek and M. Morales and M. Peleg",
  booktitle = "14th Conference on Artificial Intelligence in Medicine (AIME2013)",
  publisher = "Springer",
}

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