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  • 标题:Top data mining tools for the healthcare industry
  • 本地全文:下载
  • 作者:Judith Santos-Pereira ; Le Gruenwald ; Jorge Bernardino
  • 期刊名称:Journal of King Saud University @?C Computer and Information Sciences
  • 印刷版ISSN:1319-1578
  • 出版年度:2022
  • 卷号:34
  • 期号:8
  • 页码:4968-4982
  • 语种:English
  • 出版社:Elsevier
  • 摘要:The healthcare industry has become increasingly challenging, requiring retrieval of knowledge from large amounts of complex data to find the best treatments. Several works have suggested the use of Data Mining tools to overcome the challenges; however, none of them has suggested the best tool to do so. To fill this gap, this paper presents a survey of popular open-source data mining tools in which data mining tool selection criteria based on healthcare application requirements is proposed and the best ones using the proposed selection criteria are identified. The following popular open-source data mining tools are assessed: KNIME, R, RapidMiner, Scikit-learn, and Spark. The study shows that KNIME and RapidMiner provide the largest coverage of healthcare data mining requirements.
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