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Research on Improved Apriori Algorithm Based on Data Mining in Electronic Cases

Author

Listed:
  • Xiaoli Wang

    (Mudanjiang Medical University, Mudanjiang, China)

  • Kui Su

    (Mudanjiang Medical University, Mudanjiang, China)

  • Lirong Su

    (Mudanjiang Medical University, Mudanjiang, China)

Abstract

This article makes progress of a commonly used Apriori algorithm, and proposes a new Apriori algorithm based on event ID. In this article, association rules are gained from massive medical data through the new Apriori algorithm. This article proposes and then uses the association rules in the prediction system. This article aims at making the lifestyle-related diseases prediction system provide better service for people, for families and for the whole society. The prediction system can automatically give out health-related information of the user after the person's basic information is put in, and it would also give out some pieces of valuable advice according to the resultant data, helping people realize self-determinant health engagement.

Suggested Citation

  • Xiaoli Wang & Kui Su & Lirong Su, 2019. "Research on Improved Apriori Algorithm Based on Data Mining in Electronic Cases," International Journal of Healthcare Information Systems and Informatics (IJHISI), IGI Global, vol. 14(3), pages 16-28, July.
    • Handle: RePEc:igg:jhisi0:v:14:y:2019:i:3:p:16-28
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