Incorporating Fuzzy Logic in Object-Relational Mapping Layer for Flexible Medical Screenings

  • Bożena Małysiak-Mrozek
  • Hanna Mazurkiewicz
  • Dariusz Mrozek
Part of the Studies in Big Data book series (SBD, volume 40)


Introduction of fuzzy techniques in database querying allows for flexible retrieval of information and inclusion of imprecise expert knowledge into the retrieval process. This is especially beneficial while analyzing collections of patients’ biomedical data, in which similar results of laboratory tests may lead to the same conclusions, diagnoses, and treatment scenarios. Fuzzy techniques for data retrieval can be implemented in various layers of database client-server architecture. However, since in the last decade, the development of real-life database applications is frequently based on additional object-relational mapping (ORM) layers, inclusion of fuzzy logic in data analysis remains a challenge. In this paper, we show our extensions to the Doctrine ORM framework that supply application developers with the possibility of fuzzy querying against collections of crisp data stored in relational databases. Performance tests prove that these extensions do not introduce a significant slowdown while querying data and can be successfully used in development of applications that benefit from fuzzy information retrieval.


Databases Fuzzy sets Fuzzy logic Querying Information retrieval Biomedical data analysis Object-relational mapping ORM 



This work was supported by Statutory Research funds of Institute of Informatics, Silesian University of Technology, Gliwice, Poland (grant No BK-230/RAu2/2017).


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Bożena Małysiak-Mrozek
    • 1
  • Hanna Mazurkiewicz
    • 1
  • Dariusz Mrozek
    • 1
  1. 1.Institute of InformaticsSilesian University of TechnologyGliwicePoland

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