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Decision Support Systems in Health Care -- Velocity of Apriori Algorithm...EFMI Special Topic Conference, 2017, Israel

The amount of stored data in health information systems can reach teraand petabytes and application of specific algorithms in the field of data mining makes finding useful information suitable for making quality business decisions. A frequently used method for determining the rules of the relationsh...

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Published in:Studies in Health Technology & Informatics Vol. 244; pp. 53 - 58
Main Authors: SOMEK, Mario, HERCIGONJA-SZEKERES, Mira
Format: proceedings tables/charts Journal Article
Published: Sage Publications Inc. 2017
Online Access:View this record in EBSCOhost
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      issn: 09269630
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      dt: 2017
      vid: 244
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      pub: Sage Publications Inc.
      place: Thousand Oaks, California
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        10.3233/978-1-61499-824-2-53
        125843747
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        atl: Decision Support Systems in Health Care -- Velocity of Apriori Algorithm...EFMI Special Topic Conference, 2017, Israel
      aug:
        au:
          SOMEK, Mario
          HERCIGONJA-SZEKERES, Mira
        affil: University of Applied Health Sciences, Zagreb, Croatia
      sug:
        subj:
          Algorithms
          Decision Support Systems, Clinical
          Software
          Congresses and Conferences Israel
          Israel
      ab: The amount of stored data in health information systems can reach teraand petabytes and application of specific algorithms in the field of data mining makes finding useful information suitable for making quality business decisions. A frequently used method for determining the rules of the relationship between attributes is the Association rule by applying Apriori algorithm. Lack of basic Apriori algorithm is derived from the slow work due to multiple scanned data sets. By examining the speed of generating the basic rules in relation to the improved Apriori algorithm by using software RapidMiner confirmed that the time required to generate rules for Improved algorithm is shorter, the rules are quickly generated particularly for large data sets, which is an advantage for making decisions.
      pubtype: Academic Journal
      doctype:
        proceedings
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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