Identifying significant associations using free text problem summary lists in a clinical data repository.

David A Hanauer, Daniel R Rhodes, Arul M Chinnaiyan
Author Information
  1. David A Hanauer: Department of Pediatrics and Comprehensive Cancer Center, University of Michigan Medical School, Ann Arbor, Michigan, USA.

Abstract

Recent studies have been seeking common signatures in gene expression profiles in order to find novel associations. We chose to test the extensibility of a tool created to perform association analyses of gene expression signatures by applying the same technique to problem summary lists. Both commonly known as well as less known associations were found using this technique.

MeSH Term

Gene Expression Profiling
Humans
Information Storage and Retrieval
Medical Records, Problem-Oriented

Word Cloud

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