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180702 r ||| eng |
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|a Paynter, Robin
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|a EPC methods: An exploration of the use of text-mining software in systematic reviews
|h Elektronische Ressource
|c prepared for Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services ; prepared by Scientific Resource Center ; investigators, Robin Paynter, Lionel L. Bañez, Elise Berliner, Eileen Erinoff, Jennifer Lege-Matsuura, Shannon Potter, Stacey Uhl
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|a Exploration of the use of text-mining software in systematic reviews
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| 260 |
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|a Rockville, MD
|b Agency for Healthcare Research and Quality, U.S. Department of Health and Human Services
|c 2016, April 2016
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|a 1 PDF file (various pagings)
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|a Includes bibliographical references
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| 653 |
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|a Data Mining
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| 653 |
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|a Review Literature as Topic
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| 653 |
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|a Software
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| 710 |
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|a Scientific Resource Center (Portland, Or.)
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| 710 |
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|a United States
|b Agency for Healthcare Research and Quality
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| 041 |
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|a eng
|2 ISO 639-2
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| 989 |
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|b NCBI
|a National Center for Biotechnology Information
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|a Research white paper
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|u https://www.ncbi.nlm.nih.gov/books/NBK362044
|3 Volltext
|n NLM Bookshelf Books
|3 Volltext
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|a 800
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| 520 |
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|a RESULTS: The literature review identified 122 articles that met inclusion criteria, including two recent systematic reviews on the use of text-mining tools in the screening and data abstraction steps of systematic reviews. In addition to these two steps, a preliminary exploration of the literature on searching and other less-studied steps are presented. Support for the use of text-mining was strong amongst the KIs overall, though most KIs noted some performance caveats and/or areas in which further research is necessary. We evaluated 111 text-mining tools identified from the literature review and KI interviews. CONCLUSIONS: Text-mining tools are currently being used within several systematic review organizations for a variety of review processes (e.g., searching, screening abstracts), and the published evidence-base is growing fairly rapidly in breadth and levels of evidence.
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|a Several outstanding questions remain for future empirical research to address regarding the reliability and validity of using these emerging technologies across a variety of review processes and whether these generalize across the scope of review topics. Guidance on reporting the use of these tools would be useful
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|a OBJECTIVE: This project's goal was to provide a preliminary sketch of the use of text-mining tools as an emerging methodology within a number of systematic review processes. We sought to provide information addressing pressing questions individuals and organizations face when considering utilizing text-mining tools. METHODS: We searched the literature to identify and summarize research on the use of text-mining tools within the systematic review context. We conducted telephone interviews with Key Informants (KIs; n=8) using a semi-structured instrument and subsequent qualitative analysis to explore issues surrounding the implementation and use of text-mining tools. Lastly, we compiled a list of text-mining tools to support systematic review methods and evaluated the tools using an informal descriptive appraisal tool.
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