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Reply to Hausner et al. Re: use of text mining tools in the development of search strategies—comparison of different approaches

Journal of clinical epidemiology, 2022-09, Vol.149, p.256-257 [Peer Reviewed Journal]

2022 Elsevier Inc. ;2022. Elsevier Inc. ;ISSN: 0895-4356 ;EISSN: 1878-5921 ;DOI: 10.1016/j.jclinepi.2022.05.010 ;PMID: 35688326

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  • Title:
    Reply to Hausner et al. Re: use of text mining tools in the development of search strategies—comparison of different approaches
  • Author: Paynter, Robin A. ; Featherstone, Robin ; Stoeger, Elizabeth ; Fiordalisi, Celia ; Voisin, Christiane ; Adam, Gaelen P.
  • Subjects: Data mining
  • Is Part Of: Journal of clinical epidemiology, 2022-09, Vol.149, p.256-257
  • Description: Studied freely available TMTs to increase real world SR applicability. Point 1: selection and application of text-mining tools We are happy to agree it is entirely possible that our team would have achieved similar results if we had access to either of the fee-based software packages (i.e., SimStat/WordStat or the R Text Mining Package) used by Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen (Institute for Quality and Efficiency in Health Care) information specialists in their research along with their training and support [1–3]. Point 4: publication of further information The requested information would indeed make an interesting additional study; however, we did not systematically collect these, so are unable to provide them.
  • Publisher: United States: Elsevier Inc
  • Language: English
  • Identifier: ISSN: 0895-4356
    EISSN: 1878-5921
    DOI: 10.1016/j.jclinepi.2022.05.010
    PMID: 35688326
  • Source: ProQuest Central
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