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Efficient Genetic Algorithm for Breast Cancer Diagnosis

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Information Technology in Biomedicine (ITIB 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 762))

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Abstract

In almost all datasets some number of abnormal observations is present. Such outliers may affect the process of data analysis. However several methods of outlier detection already exist, there is still a need to look for a new, more effective ones. In this paper we propose a set of objectives that allows to efficiently identify outliers with the use of multiobjective genetic algorithm. Conducted research shown that such a method can be successfully used with the most common genetic algorithms designed for multiobjective optimization. The results of tests, which were conducted on the set of medical data from the repository, indicate that our method can be successfully applied to the medical problem.

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Acknowledgement

This work was supported by a grant of the Dean of the Faculty of Technical Physics, Information Technology and Applied Mathematics, Lodz University of Technology. The dataset used in our research was taken from the UCI Machine Learning Repository [21].

Author information

Authors and Affiliations

  1. Lodz University of Technology, Lodz, Poland

    Lukasz Chomatek & Agnieszka Duraj

Authors
  1. Lukasz Chomatek
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  2. Agnieszka Duraj
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Corresponding author

Correspondence to Lukasz Chomatek .

Editor information

Editors and Affiliations

  1. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Ewa Pietka

  2. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Pawel Badura

  3. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Jacek Kawa

  4. Faculty of Biomedical Engineering, Silesian University of Technology, Zabrze, Poland

    Wojciech Wieclawek

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Chomatek, L., Duraj, A. (2019). Efficient Genetic Algorithm for Breast Cancer Diagnosis. In: Pietka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technology in Biomedicine. ITIB 2018. Advances in Intelligent Systems and Computing, vol 762. Springer, Cham. https://doi.org/10.1007/978-3-319-91211-0_6

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