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Integrating data mining with case-based reasoning for chronic diseases prognosis and diagnosis

This article discusses the integration of data mining and case-based reasoning to improve the prognosis and diagnosis of chronic diseases. The objective is to use data mining techniques to extract meaningful rules from health examination data and apply them to specific chronic diseases prognosis. Case-based reasoning is then used to support the diagnosis and treatment of these diseases within a system.

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Integrating data mining with case-based reasoning for chronic diseases prognosis and diagnosis

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  1. Integrating data mining with case-based reasoning for chronic diseases prognosis and diagnosis Advisor ：Dr. Hsu Presenter：Chien-Shing Chen Author: Mu-Jung Huang Mu-Yen Chen Show-Chin Lee 2006, Expert Systems with Applications

  2. Outline • Motivation • Objective • Introduction • CDPD architecture • Conclusions • Personal Opinion

  3. Motivation • The threats to People’s health from chronic diseases are always exist and increasing gradually. • construct a model to integrate data mining (DM) and case-based reasoning (CBR)

  4. Objective • adopting data mining techniques to discover the implicit meaning from rules from health examination data • using the extracted rules for the specific chronic diseases prognosis • employing CBR to support the chronic diseases diagnosis(診斷) and treatments(治療) • expanding these process to work within a system

  5. Introduction Characterize a case How cases are stored in the case library Adapting old solutions to meet new demands, using old cases to explain new situations retrieve from library New problem is solved-> store it Old knowledge need to be fixed to fit the new one

  6. Introduction

  7. Modify the retrieved case to solve the problems of the new case

  8. implementation • after preprocess, 15,751 records, 28 fields • class level: the target chronic diseases, stroke, cardiopathy, hypertension, and diabetes mellitus, are also classified,

  9. Performance • stroke:

  10. Performance

  11. Performance

  12. Performance

  13. Performance

  14. Conclusion • helpful • integration • retrieve the most similar case from the case library • CDPD

  15. Opinion • Drawback • nature things • Application • existing professional knowledge well, anything what you want could be done. • Future Work

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