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We automatically structure and compare the content of eligibility criteria of clinical tis frank mccourt pdf free download. Our method for comparing criteria restrictiveness obtains high precision.

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Our library of structured criteria can support trial and population comparison. It can be browsed with the fine-grained queries. Our library visualization exposes correlations between criteria, trials and concepts. Patient recruitment is one of the most important barriers to successful completion of clinical trials and thus to obtaining evidence about new methods for prevention, diagnostics and treatment. The reason is that recruitment is effort consuming. The work we describe in this paper aims to support the comparison of population under study in different trials, and the design of eligibility criteria for new trials. Additionally, structured eligibility criteria allow us to propose suggestions for relaxation of criteria to remove potentially unnecessarily restrictive conditions.

We thereby increase the recruitment potential and generalizability of a trial. Our method for automated structuring of criteria enables us to identify related conditions and to compare their restrictiveness. The comparison is based on the general meaning of criteria, comprised of commonly occurring contextual patterns, medical concepts and constraining values. These are automatically identified using our pattern detection algorithm, state of the art ontology annotators and semantic taggers. The comparison uses predefined relations between the patterns, concept equivalences defined in medical ontologies, and threshold values.