Skip to main content
SpringerLink
Log in

Cost Sensitive Hierarchical Classifiers for Non-invasive Recognition of Liver Fibrosis Stage

  • Conference paper
Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 226))

Abstract

Liver Fibrosis caused by the Hepatitis Virus type C (HCV) may be a serious life-threatening condition if is not diagnosed and treated on time. Our previous research proved that it is possible to estimate liver fibrosis stage in patients with diagnosed HCV only using blood tests. The aim of our research is to find a safe and non-invasive but also inexpensive diagnostic method. As not all blood tests are equally expensive (not only in meaning of money, but also time of analysis), this article introduces a Cost Factor to the hierarchical classifiers. Our classifier has been based on a C4.5 decision tree building algorithm enhanced with a modified EG2 algorithm for maintaining a cost limit.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 259.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 329.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bedossa, P., Dargre, D., Paradis, V.: Sampling variability of liver fibrosis in chronic hepatitis. Hepatology 38, 1449–1457 (2003)

    Google Scholar 

  2. Bedossa, P., Poynard, T.: An algorithm for the grading of activity in chronic hepatitis. The Metavir Cooperative Study Group 24, 289–293 (1996)

    Google Scholar 

  3. BioPredictive. Website, http://www.biopredictive.com/intl/physician/fibrotest-for-hcv/

  4. Burduk, R., Zmyślony, M.: Decomposition of classification task with selection of classifiers on the medical diagnosis example. In: Corchado, E., Snášel, V., Abraham, A., Woźniak, M., Graña, M., Cho, S.-B. (eds.) HAIS 2012, Part II. LNCS, vol. 7209, pp. 569–577. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  5. Castéra, L.: Non invasive assessment of liver fibrosis in chronic hepatitis. Liver International 5(2), 625–634 (2002)

    Google Scholar 

  6. Siemens Healthcare. Website, http://healthcare.siemens.com/clinical-specialities/liver-disease

  7. iQur Ltd. Website, http://www.iqur.com/ELFTest.html

  8. Krawczyk, B., Woźniak, M., Orczyk, T., Porwik, P., Musialik, J., Blońska-Fajfrowska, B.: Classification techniques for non-invasive recognition of liver fibrosis stage. Journal of Medical Informatics & Technologies 20, 121–127 (2012)

    Google Scholar 

  9. Nuenz, M.: The use of background knowledge in decision tree induction. Machine Learning 6, 231–250 (1991)

    Google Scholar 

  10. Orczyk, T., Paĺys, M., Porwik, P., Musialik, J., Blońska-Fajfrowska, B.: Simple and non-invasive liver fibrosis stage prediction method. Journal of Medical Informatics & Technologies 17, 227–232 (2011)

    Google Scholar 

  11. Penar, W., Woźniak, M.: Cost-sensitive methods of constructing hierarchical classifiers. Expert Systems 27(3), 146–155 (2010)

    Article  Google Scholar 

  12. Podolak, I.T., Roman, A.: Risk function estimation for subproblems in a hierarchical classifier. Pattern Recognition Letters 32(15), 2136–2142 (2011)

    Article  Google Scholar 

  13. Quinlan, J.R.: Induction of decision trees. Machine Learning 1(1), 81–106 (1986)

    Google Scholar 

  14. Quinlan, J.R.: C4.5: Programs for Machine Learning. Morgan Kaufmann Series in Machine Learning. Morgan Kaufmann Publishers (1993)

    Google Scholar 

  15. Regev, A., Berho, M., Jeffers, L.J., Milikowski, C., Molina, E.G., Pyrsopoulos, N.T., Feng, Z.Z., Reddy, K.R., Schiff, E.R.: Sampling error and intraobserver variation in liver biopsy in patients with chronic hcv infection. The American Journal of Gastroenterology 97(10), 2614–2618 (2002)

    Article  Google Scholar 

  16. Senator, T.E.: Multi-stage classification. In: Proceedings - IEEE International Conference on Data Mining, ICDM, pp. 386–393 (2005)

    Google Scholar 

  17. R Development Core Team. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2008)

    Google Scholar 

  18. Ting, K.M.: An instance-weighting method to induce cost-sensitive trees. IEEE Transactions on Knowledge and Data Engineering 14(3), 659–665 (2002)

    Article  Google Scholar 

  19. Weiss, Y., Elovici, Y., Rokach, L.: The cash algorithm-cost-sensitive attribute selection using histograms. Information Sciences 222, 247–268 (2013)

    Article  MathSciNet  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Systems and Computer Networks, Wroclaw University of Technology, Wyb. Wyspianskiego 27, 50-370, Wroclaw, Poland

    Bartosz Krawczyk & Michał Woźniak

  2. Institute of Computer Science, University of Silesia, Bedzinska 39, 41-200, Sosnowiec, Poland

    Tomasz Orczyk & Piotr Porwik

Authors
  1. Bartosz Krawczyk
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Michał Woźniak
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tomasz Orczyk
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Piotr Porwik
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Bartosz Krawczyk .

Editor information

Editors and Affiliations

  1. , Department of Systems and Computer, Wroclaw University of Technology, WybrzezeWyspianskiego St 27, Wroclaw, 50-370, Poland

    Robert Burduk

  2. , Department of Systems and Computer, Wroclaw University of Technology, WybrzezeWyspianskiego St 27, Wroclaw, 50-370, Poland

    Konrad Jackowski

  3. , Department of Systems and Computer, Wroclaw University of Technology, WybrzezeWyspianskiego St 27, Wroclaw, 50-370, Poland

    Marek Kurzynski

  4. , Department of Systems and Computer, Wroclaw University of Technology, WybrzezeWyspianskiego St 27, Wroclaw, 50-370, Poland

    Michał Wozniak

  5. , Department of Systems and Computer, Wroclaw University of Technology, WybrzezeWyspianskiego St, Wroclaw, 50-370, Poland

    Andrzej Zolnierek

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer International Publishing Switzerland

About this paper

Cite this paper

Krawczyk, B., Woźniak, M., Orczyk, T., Porwik, P. (2013). Cost Sensitive Hierarchical Classifiers for Non-invasive Recognition of Liver Fibrosis Stage. In: Burduk, R., Jackowski, K., Kurzynski, M., Wozniak, M., Zolnierek, A. (eds) Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013. Advances in Intelligent Systems and Computing, vol 226. Springer, Heidelberg. https://doi.org/10.1007/978-3-319-00969-8_63

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-00969-8_63

  • Publisher Name: Springer, Heidelberg

  • Print ISBN: 978-3-319-00968-1

  • Online ISBN: 978-3-319-00969-8

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation