A human-computer collaborative approach to identifying common data elements in clinical trial eligibility criteria.

ABSTRACT:

Objective

To identify Common Data Elements (CDEs) in eligibility criteria of multiple clinical trials studying the same disease using a human-computer collaborative approach.

Design

A set of free-text eligibility criteria from clinical trials on two representative diseases, breast cancer and cardiovascular diseases, was sampled to identify disease-specific eligibility criteria CDEs. In this proposed approach, a semantic annotator is used to recognize Unified Medical Language Systems (UMLSs) terms within the eligibility criteria text. The Apriori algorithm is applied to mine frequent disease-specific UMLS terms, which are then filtered by a list of preferred UMLS semantic types, grouped by similarity based on the Dice coefficient, and, finally, manually reviewed.

Measureme

SUBMITTER: Luo Z 

PROVIDER: S-EPMC3524400 | biostudies-literature | 2013 Feb

REPOSITORIES: biostudies-literature