Literature DB >> 18999072

Evaluation of the google search appliance for patient cohort discovery.

Ryan Oberg1, Luke Rasmussen, John Melski, Peggy Peissig, Justin Starren.   

Abstract

Rapid location of patient cohorts with specific attributes is critical to accelerating translational research. Given the ever-increasing popularity of web search engines for information retrieval, we performed an evaluation the Google Search Appliance (GSA) as a potential tool for performing a fast and simple retrospective analysis of our patient record for researchers discovering study cohorts. Overall, the GSA did not provide a significant advantage over conventional database queries. Possible reasons for this are presented.

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Year:  2008        PMID: 18999072

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  3 in total

1.  The design and implementation of an open-source, data-driven cohort recruitment system: the Duke Integrated Subject Cohort and Enrollment Research Network (DISCERN).

Authors:  Jeffrey M Ferranti; William Gilbert; Jonathan McCall; Howard Shang; Tanya Barros; Monica M Horvath
Journal:  J Am Med Inform Assoc       Date:  2011-09-23       Impact factor: 4.497

Review 2.  A review of approaches to identifying patient phenotype cohorts using electronic health records.

Authors:  Chaitanya Shivade; Preethi Raghavan; Eric Fosler-Lussier; Peter J Embi; Noemie Elhadad; Stephen B Johnson; Albert M Lai
Journal:  J Am Med Inform Assoc       Date:  2013-11-07       Impact factor: 4.497

Review 3.  Employing computers for the recruitment into clinical trials: a comprehensive systematic review.

Authors:  Felix Köpcke; Hans-Ulrich Prokosch
Journal:  J Med Internet Res       Date:  2014-07-01       Impact factor: 5.428

  3 in total

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