Decision Tree Driven Rule Induction for Heart Disease Prediction Model: Korean National Health and Nutrition Examinations Survey V-1

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


Heart disease has the highest rates of death in non-communicable disease and there have been much research on heart disease. Even though there is recognition for importance of heart disease prediction, related studies are insufficient. Therefore, to develop heart disease prediction model for Korean, we suggest data mining driven rule induction for heart disease prediction in this paper. Proposed method suggest heart disease prediction model by applying decision tree driven rule induction based on data set from Korean National Health and Nutrition Examinations Survey V-1 (KNHANES V-1). The prediction model is expected contribute to Korea’s heart disease prediction.


Data mining Heart disease prediction Decision tree Rule induction KNHANES V-1 



This work was supported by the R&D Program of MKE/KEIT [10032115, Development of Digital TV based u-Health System using AI].


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Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Jae-Kwon Kim
    • 1
  • Eun-Ji Son
    • 2
  • Young-Ho Lee
    • 2
  • Dong-Kyun Park
    • 3
  1. 1.School of Computer Science and Information EngineeringInha UniversityIncheonSouth Korea
  2. 2.School of Information TechnologyGachon UniversityIncheonSouth Korea
  3. 3.u-Healthcare CenterGachon University Gil HospitalIncheonSouth Korea

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