Knowledge Services Using Rule-Based Formalization for Eligibility Criteria of Clinical Trials

Research output: Scientific - peer-reviewConference contribution

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.
Original languageEnglish
Title of host publicationHealth Information Science - 5th International Conference, HIS 2016, Proceedings
PublisherSpringer/Verlag
Pages49-61
Number of pages13
Volume10038 LNCS
ISBN (Print)9783319483344
DOIs
StatePublished - 2016
Event5th International Conference on Health Information Science, HIS 2016 - Shanghai, China

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer
Volume10038 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Conference on Health Information Science, HIS 2016
CountryChina
CityShanghai
Period5/11/167/11/16

Cite this

Huang, Z., Hu, Q., ten Teije, A. C. M., van Harmelen, F. A. H., & Ait-Mokhtar, S. (2016). Knowledge Services Using Rule-Based Formalization for Eligibility Criteria of Clinical Trials. In Health Information Science - 5th International Conference, HIS 2016, Proceedings (Vol. 10038 LNCS, pp. 49-61). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10038 LNCS). Springer/Verlag. DOI: 10.1007/978-3-319-48335-1_6

Huang, Z.; Hu, Q.; ten Teije, A.C.M.; van Harmelen, F.A.H.; Ait-Mokhtar, S. / Knowledge Services Using Rule-Based Formalization for Eligibility Criteria of Clinical Trials.

Health Information Science - 5th International Conference, HIS 2016, Proceedings. Vol. 10038 LNCS Springer/Verlag, 2016. p. 49-61 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10038 LNCS).

Research output: Scientific - peer-reviewConference contribution

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Huang, Z, Hu, Q, ten Teije, ACM, van Harmelen, FAH & Ait-Mokhtar, S 2016, Knowledge Services Using Rule-Based Formalization for Eligibility Criteria of Clinical Trials. in Health Information Science - 5th International Conference, HIS 2016, Proceedings. vol. 10038 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10038 LNCS, Springer/Verlag, pp. 49-61, 5th International Conference on Health Information Science, HIS 2016, Shanghai, China, 5-7 November. DOI: 10.1007/978-3-319-48335-1_6

Knowledge Services Using Rule-Based Formalization for Eligibility Criteria of Clinical Trials. / Huang, Z.; Hu, Q.; ten Teije, A.C.M.; van Harmelen, F.A.H.; Ait-Mokhtar, S.

Health Information Science - 5th International Conference, HIS 2016, Proceedings. Vol. 10038 LNCS Springer/Verlag, 2016. p. 49-61 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10038 LNCS).

Research output: Scientific - peer-reviewConference contribution

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Huang Z, Hu Q, ten Teije ACM, van Harmelen FAH, Ait-Mokhtar S. Knowledge Services Using Rule-Based Formalization for Eligibility Criteria of Clinical Trials. In Health Information Science - 5th International Conference, HIS 2016, Proceedings. Vol. 10038 LNCS. Springer/Verlag. 2016. p. 49-61. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). Available from, DOI: 10.1007/978-3-319-48335-1_6