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Conference Papers Year : 2017

Numerical eligibility criteria in clinical protocols: annotation, automatic detection and interpretation

Abstract

Clinical trials are fundamental for evaluating therapies and diagnosis techniques. Yet, recruitment of patients remains a real challenge. Eligibility criteria are related to terms but also to patient laboratory results usually expressed with numerical values. Both types of information are important for patient selection. We propose to address the processing of numerical values. A set of sentences extracted from clinical trials are manually annotated by four annotators. Four categories are distinguished: C (concept), V (numerical value), U (unit), O (out position). According to the pairs of annotators, the inter-annotator agreement on the whole annotation sequence CV U goes up to 0.78 and 0.83. Then, an automatic method using CFRs is exploited for creating a supervised model for the recognition of these categories. The obtained F-measure is 0.60 for C, 0.82 for V , and 0.76 for U .
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Dates and versions

hal-01618930 , version 1 (18-10-2017)
hal-01618930 , version 2 (21-11-2017)

Identifiers

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Vincent Claveau, Lucas Emanuel Silva Oliveira, Guillaume Bouzillé, Marc Cuggia, Claudia Maria Cabral Moro, et al.. Numerical eligibility criteria in clinical protocols: annotation, automatic detection and interpretation. AIME 2017 - 16th Conference in Artificial Intelligence in Medecine, Jun 2017, Vienne, Austria. pp.203-208, ⟨10.1007/978-3-319-59758-4_22⟩. ⟨hal-01618930v2⟩
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