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)


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.


CDSS Data mining Fuzzy logic Heart disease FHPM 



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


  1. 1.
    World Health Organization (2010) The world health report 2010. Retrieved Nov 2010
  2. 2.
    Anooj PK (2012) Clinical decision support system: risk level prediction of heart disease using decision tree fuzzy rules. Int J IJRRCS 3(3):1659–1667Google Scholar
  3. 3.
    Garg AX, Adhikari NKJ, McDonald H et al (2005) Effects of computerized clinical decision support systems on practitioner performance and patient outcomes. J Am Med Assoc 293(10):1223–1238CrossRefGoogle Scholar
  4. 4.
    Lee DY, Rhee EJ, Choi E et al (2008) Comparison of the predictability of cardiovascular disease risk according to different metabolic syndrome criteria of American heart association/national heart, Lung, and Blood institute and international Diabetes federation in Korean men. J Korean Diabetes 32(4):317–327Google Scholar
  5. 5.
    Vahid K, Gholam AM (2010) A fuzzy-evidential hybrid inference engine for coronary heart disease risk assessment. Int J Expert Syst Appl 37(12):8536–8542Google Scholar
  6. 6.
    Korea Centers for Disease Control and Prevention (2010) 5th Korean national health and nutrition examinations survey (KNHANES V-1). Korea Centers for Disease Control and PreventionGoogle Scholar

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

Personalised recommendations