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International Conference on Future Data and Security Engineering

FDSE 2018: Future Data and Security Engineering pp 299–309Cite as

Comprehensive Review of Classification Algorithms for Medical Information System

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

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.

Keywords

  • Classification
  • Decision tree
  • Decision system
  • Information system

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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

    CrossRef  Google Scholar 

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

    CrossRef  MATH  Google Scholar 

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

    CrossRef  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)

    CrossRef  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

    CrossRef  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)

    CrossRef  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

    CrossRef  MATH  Google Scholar 

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

    CrossRef  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

    CrossRef  MATH  Google Scholar 

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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.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Division of Biocybernetics and Biomedical Engineering, Bialystok University of Technology, ul. Wiejska 45c, 15-351, Bialystok, Poland

    Anna Kasperczuk & Agnieszka Dardzinska

Authors
  1. Anna Kasperczuk
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  2. Agnieszka Dardzinska
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Corresponding author

Correspondence to Agnieszka Dardzinska .

Editor information

Editors and Affiliations

  1. Ho Chi Minh City University of Technology, Ho Chi Minh, Vietnam

    Tran Khanh Dang

  2. Johannes Kepler University of Linz, Linz, Austria

    Josef Küng

  3. Johannes Kepler University of Linz, Linz, Austria

    Prof. Dr. Roland Wagner

  4. Ho Chi Minh City University of Technology, Ho Chi Minh, Vietnam

    Nam Thoai

  5. Hosei University, Tokyo, Japan

    Makoto Takizawa

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Kasperczuk, A., Dardzinska, A. (2018). Comprehensive Review of Classification Algorithms for Medical Information System. In: Dang, T., Küng, 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

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

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