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Application of Association Rules to Classify IBD Patients

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Foundations of Intelligent Systems (ISMIS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13515))

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Abstract

The characterization of inflammatory bowel diseases (IBD) is not always easy. In particular cases of titled lesions, it is difficult for physicians to differentiate between UC and CD. There-fore, it is important to search for new differentiating symptoms. The obtained information will deepen the current knowledge about UC and CD. For this reason, finding an optimal classifier to support further analysis of medical data is a decisive factor for correct patient assignment. Built system using CBA method with very high efficiency is able to predict which group of diseases a new, undiagnosed patient belongs to (sensitivity 94.1%, specificity 85.9%). The built model can be an excellent method to support physicians in decision making.

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Acknowledgements

This research was funded by Ministry of Science and Higher Education in Poland, grant number W/WM-IIB/3/2021 and WZ/WM-IIM/3/2020.

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Authors and Affiliations

  1. Department of Mechanics and Applied Computer Science, Bialystok University of Technology, Wiejska 45c, 15-351, Bialystok, Poland

    Agnieszka Dardzinska

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

    Anna Kasperczuk

Authors
  1. Agnieszka Dardzinska
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  2. Anna Kasperczuk
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Corresponding author

Correspondence to Anna Kasperczuk .

Editor information

Editors and Affiliations

  1. Università degli Studi di Bari Aldo Moro, Bari, Italy

    Michelangelo Ceci

  2. Università della Calabria, Rende, Italy

    Sergio Flesca

  3. Università Federico II di Napoli, Naples, Italy

    Elio Masciari

  4. ICAR-CNR, Rende, Italy

    Giuseppe Manco

  5. University of North Carolina, Charlotte, NC, USA

    Zbigniew W. Raś

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Dardzinska, A., Kasperczuk, A. (2022). Application of Association Rules to Classify IBD Patients. In: Ceci, M., Flesca, S., Masciari, E., Manco, G., Raś, Z.W. (eds) Foundations of Intelligent Systems. ISMIS 2022. Lecture Notes in Computer Science(), vol 13515. Springer, Cham. https://doi.org/10.1007/978-3-031-16564-1_41

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  • DOI: https://doi.org/10.1007/978-3-031-16564-1_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-16563-4

  • Online ISBN: 978-3-031-16564-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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