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Data Mining-Driven Chronic Heart Disease for Clinical Decision Support System Architecture in Korea

  • Eun-Ji Son
  • Jae-Kwon Kim
  • Young-Ho Lee
  • Eun-Young Jung
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 215)

Abstract

We present Clinical Decision Support System (CDSS) architecture to implement extensible and interoperable clinical decision support service in perspective of heart study using data mining. In our architecture, intelligence agent engine is critical component for implementing intelligent service using data mining. In this paper, we suggested Fuzzy logic driven Heart risk factor Prediction Model (FHPM) architecture in CDSS. In this CDSS architecture, components for intelligent service with missing value processing logic, Fuzzy linguistic and rule induction method are consisted. FHPM can create chronic heart disease guideline using Korean Data set. FHPM can provide clinical decision support services for the heart disease prediction for Korean.

Keywords

CDSS Data mining Fuzzy logic Heart disease FHPM 

Notes

Acknowledgments

This study was supported by a grant of the Korean Health Technology R&D Project, Ministry of Health & Welfare, Republic of Korea (A11202).

References

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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Eun-Ji Son
    • 1
  • Jae-Kwon Kim
    • 2
  • Young-Ho Lee
    • 1
  • Eun-Young Jung
    • 3
  1. 1.School of Information TechnologyGachon UniversityYeonsu-guSouth Korea
  2. 2.School of Computer Science & Information EngineeringInha UniversityNam-guSouth Korea
  3. 3.U-Healthcare CenterGachon University Gil HospitalNamdong-guSouth Korea

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