Skip to main content

Comprehensive Review of Classification Algorithms for Medical Information System

  • Conference paper
  • First Online:
Future Data and Security Engineering (FDSE 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11251))

Included in the following conference series:

Abstract

Nowadays, the Internet and information systems become an integral part of everyday life. The trend of using advanced recommendation systems is still growing in various areas, also in medicine. Two of the diseases where diagnosis is a big problem for specialists are colon disease and Crohn’s disease. The course of the disease strongly resembles other diseases in the large intestine, so it became extremely important to help doctors and find symptoms that would clearly indicate the colon disease, excluding others. In order to find rules that distinguish these two diseases, together data mining and statistical methods were mixed and used.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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

References

  1. Breiman, L., Friedman, J.H., Olshen, R.A., Stone, C.J.: Classification and Regression Trees. Wadsworth International Group, Belmont (1984)

    MATH  Google Scholar 

  2. Cheng, J., Greiner, R.: Learning Bayesian belief network classifiers: algorithms and system. In: Stroulia, E., Matwin, S. (eds.) AI 2001. LNCS (LNAI), vol. 2056, pp. 141–151. Springer, Heidelberg (2001). https://doi.org/10.1007/3-540-45153-6_14

    Chapter  Google Scholar 

  3. Dardzinska, A.: Action Rules Mining. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-35650-6

    Book  MATH  Google Scholar 

  4. Fawcett, T.: An introduction to ROC analysis. Pattern Recogn. Lett. 27, 861–874 (2006)

    Article  Google Scholar 

  5. Frawley, W., Piatetsky-Shapiro, G., Matheus, C.: Knowledge discovery in databases, an overview. Knowl. Disc. Databases 1–27 (1991)

    Google Scholar 

  6. Hand, D., Mannila, H., Smyth, P.: Eksploracja danych. Wydawnictwa Naukowo – Techniczne, Warszawa, 35–61, 91–127, 181–201 (2005)

    Google Scholar 

  7. Kasperczuk, A., Dardzinska, A.: Comparative evaluation of the different data mining techniques used for the medical database. Acta Mechanica et Automatica 10(3), 233–238 (2016)

    Article  Google Scholar 

  8. Kohavi, R.: A study of cross-validation and bootstrap for accuracy estimation and model selection. In: Proceedings of the International Joint Conference on Artificial Intelligence, vol. 2, pp. 1137–1143 (1995)

    Google Scholar 

  9. Powers, D.M.W.: Evaluation: from precision, recall and F-measure to ROC, informedness, markedness and correlation. J. Mach. Learn. Technol. 2(1), 37–63 (2011)

    MathSciNet  Google Scholar 

  10. Quinlan, J.R.: Introduction of decision trees. In: Machine Learning, pp. 81–106. Kluwer Academic Publishers (1986)

    Google Scholar 

  11. Ras, Z.W., Dardzinska, A., Liu, X.: Rule discovery by axes-driven hyperplanes construction. In: Kłopotek, M.A., Wierzchoń, S.T., Trojanowski, K. (eds.) Intelligent Information Processing and Web Mining. Advances in Soft Computing, vol. 25. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-39985-8_62

    Chapter  Google Scholar 

  12. Ras, Z.W., Dardzinska, A., Liu, X.: System ADReD for discovering rules based on hyperplanes, special issue on selected problems in knowledge representation. Int. J. Eng. Appl. Artif. Intell. 17(4), 401–406 (2004)

    Article  Google Scholar 

  13. Raś, Z.W., Dardzińska, A.: Data security and null value imputation in distributed information systems. In: Raś, Z.W., Dardzińska, A. (eds.) Monitoring, Security, and Rescue Techniques in Multiagent Systems. Advances in Soft Computing, vol. 28. Springer, Heidelberg (2005). https://doi.org/10.1007/3-540-32370-8_9

    Chapter  MATH  Google Scholar 

  14. Stehman, S.V.: Selecting and interpreting measures of thematic classification accuracy. Remote Sens. Environ. 62(1), 77–89 (1997)

    Article  Google Scholar 

  15. Vapnik, V.: The Nature of Statistical Learning Theory. Springer, New York (1995). https://doi.org/10.1007/978-1-4757-2440-0

    Book  MATH  Google Scholar 

Download references

Acknowledgements

This work was supported by MB/WM/8/2016 and financed with use of funds for science of MNiSW. The Bioethical Commission gave the permission for the analysis and publication of our results.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Agnieszka Dardzinska .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Kasperczuk, A., Dardzinska, A. (2018). Comprehensive Review of Classification Algorithms for Medical Information System. In: Dang, T., KĂĽng, J., Wagner, R., Thoai, N., Takizawa, M. (eds) Future Data and Security Engineering. FDSE 2018. Lecture Notes in Computer Science(), vol 11251. Springer, Cham. https://doi.org/10.1007/978-3-030-03192-3_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-03192-3_23

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-03191-6

  • Online ISBN: 978-3-030-03192-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics