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

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IT Convergence and Security 2012

Part of the book series: Lecture Notes in Electrical Engineering ((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.

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References

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Acknowledgments

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

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Authors and Affiliations

  1. School of Information Technology, Gachon University, 191, Hambakmoero, Yeonsu-gu, Incheon, South Korea

    Eun-Ji Son & Young-Ho Lee

  2. School of Computer Science & Information Engineering, Inha University, 253, Yonghyun-dong, Nam-gu, Incheon, South Korea

    Jae-Kwon Kim

  3. U-Healthcare Center, Gachon University Gil Hospital, 1198, Guwold-dong, Namdong-gu, Incheon, South Korea

    Eun-Young Jung

Authors
  1. Eun-Ji Son
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  2. Jae-Kwon Kim
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  3. Young-Ho Lee
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  4. Eun-Young Jung
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Corresponding author

Correspondence to Eun-Young Jung .

Editor information

Editors and Affiliations

  1. Convergence Security, Kyoung-gi University, Suwon, Gyeonggi-do, Korea, Republic of (South Korea)

    Kuinam J. Kim

  2. Dept. of Computer Information Engineerin, Sangji University, Wonju-si Gangwon-do, Korea, Republic of (South Korea)

    Kyung-Yong Chung

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© 2013 Springer Science+Business Media Dordrecht

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Son, EJ., Kim, JK., Lee, YH., Jung, EY. (2013). Data Mining-Driven Chronic Heart Disease for Clinical Decision Support System Architecture in Korea. In: Kim, K., Chung, KY. (eds) IT Convergence and Security 2012. Lecture Notes in Electrical Engineering, vol 215. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5860-5_124

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  • DOI: https://doi.org/10.1007/978-94-007-5860-5_124

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  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-94-007-5859-9

  • Online ISBN: 978-94-007-5860-5

  • eBook Packages: EngineeringEngineering (R0)

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