Text mining for efficient search and assisted creation of clinical trials

Ioannis Korkontzelos, Tingting Mu, Angelo Restificar, Sophia Ananiadou

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    Abstract

    Clinical trials are mandatory protocols describing medical research on humans and among the most valuable sources of medical practice evidence. Searching for trials relevant to some query is laborious due to the immense number of existing protocols. Apart from search, writing new trials includes composing detailed eligibility criteria, which might be time-consuming, especially for new researchers. In this paper we present ASCOT, an efficient search application customised for clinical trials. ASCOT uses text mining and data mining methods to enrich clinical trials with metadata, that in turn serve as effective tools to narrow down search. In addition, ASCOT integrates a component for recommending eligibility criteria based on a set of selected protocols. © 2011 ACM.
    Original languageEnglish
    Title of host publicationInternational Conference on Information and Knowledge Management, Proceedings|Int Conf Inf Knowledge Manage
    Pages43-50
    Number of pages7
    DOIs
    Publication statusPublished - 2011
    EventACM 5th International Workshop on Data and Text Mining in Biomedical Informatics, DTMBIO'11, in Conjunction with the 20th ACM International Conference on Information and Knowledge Management, CIKM'11 - Glasgow
    Duration: 1 Jul 2011 → …

    Conference

    ConferenceACM 5th International Workshop on Data and Text Mining in Biomedical Informatics, DTMBIO'11, in Conjunction with the 20th ACM International Conference on Information and Knowledge Management, CIKM'11
    CityGlasgow
    Period1/07/11 → …

    Keywords

    • clinical trials
    • cluster labels
    • clustering
    • eligibility criteria
    • facet
    • term extraction
    • terms

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