Textual inference for eligibility criteria resolution in clinical trials.

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dc.contributor.authorShivade, Chaitanya
dc.contributor.authorHebert, Courtney
dc.contributor.authorLopetegui, Marcelo
dc.contributor.authorDe Marneffe, Marie-Catherine
dc.contributor.authorFosler-Lussier, Eric
dc.contributor.authorLai, Albert
dc.date.accessioned2016-05-18T17:22:26Z
dc.date.available2016-05-18T17:22:26Z
dc.date.issued2015
dc.description.abstractClinical trials are essential for determining whether new interventions are effective. In order to determine the eligibility of patients to enroll into these trials, clinical trial coordinators often perform a manual review of clinical notes in the electronic health record of patients. This is a very time-consuming and exhausting task. Efforts in this process can be expedited if these coordinators are directed toward specific parts of the text that are relevant for eligibility determination. In this study, we describe the creation of a dataset that can be used to evaluate automated methods capable of identifying sentences in a note that are relevant for screening a patient's eligibility in clinical trials. Using this dataset, we also present results for four simple methods in natural language processing that can be used to automate this task. We found that this is a challenging task (maximum F-score=26.25), but it is a promising direction for further research.
dc.identifier.citationShivade C, Hebert C, Lopetegui M, de Marneffe MC, Fosler-Lussier E, Lai AM. Textual inference for eligibility criteria resolution in clinical trials. J Biomed Inform. 2015 Dec;58 Suppl(Suppl):S211-S218
dc.identifier.urihttp://hdl.handle.net/11447/277
dc.identifier.urihttp://dx.doi.org/10.1016/j.jbi.2015.09.008
dc.language.isoen_US
dc.publisherElsevier Inc
dc.subjectClinical trials
dc.subjectElectronic health records
dc.subjectNatural language processing
dc.subjectTextual inference
dc.titleTextual inference for eligibility criteria resolution in clinical trials.
dc.typeArtículo

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