@inbook{210cc82a653b4c559a54a863de63cad2,
  title     = "Knowledge Services Using Rule-Based Formalization for Eligibility Criteria of Clinical Trials",
  abstract  = "Rule-based formalization of eligibility criteria in clinical trials have distinguished features such as declaration, easy maintenance, reusability, and expressiveness. In this paper, we present several knowledge services which can be provided by the rule-based formalization of eligibility criteria. The rule-based formalization can be generated automatically by using the logic programming Prolog with the support of NLP tools for the semantic annotation and relation extraction with medical ontologies/terminologies such as UMLS and SNOMED CT. We show how those automatically generated rule-based formalization for eligibility criteria can be used for the patient recruitment service in SemanticCT, a semantically-enabled system for clinical trials.",
  author    = "Z. Huang and Q. Hu and {ten Teije}, A.C.M. and {van Harmelen}, F.A.H. and S. Ait-Mokhtar",
  year      = "2016",
  doi       = "10.1007/978-3-319-48335-1_6",
  isbn      = "9783319483344",
  volume    = "10038 LNCS",
  series    = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
  publisher = "Springer/Verlag",
  pages     = "49--61",
  booktitle = "Health Information Science - 5th International Conference, HIS 2016, Proceedings",
}

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