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A Knowledge Graph to Analyze Clinical Patient Data

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New Trends in Database and Information Systems (ADBIS 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1850))

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Abstract

Knowledge graphs may be successfully applied to represent different types of relationships among different types of subjects. Here, we propose a Knowledge Graph model to represent patient data coming from clinical folders information. The main aim is to provide suitable classifications of patients, in order to allow a deeper understanding of possible (side) effects that the same treatment may cause on different patients. We have implemented our model using the Neo4J NoSQL database and we present some preliminary analysis, as an example of how our model can be usefully exploited.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Palermo, Palermo, Italy

    Mariella Bonomo & Francesco Ippolito

  2. Kazaam Lab S.r.l., Palermo, Italy

    Mariella Bonomo & Salvatore Morfea

Authors
  1. Mariella Bonomo
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  2. Francesco Ippolito
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  3. Salvatore Morfea
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Corresponding author

Correspondence to Mariella Bonomo .

Editor information

Editors and Affiliations

  1. Universitat Politècnica de Catalunya, Barcelona, Spain

    Alberto Abelló

  2. University of Ioannina, Ioannina, Greece

    Panos Vassiliadis

  3. Universitat Politècnica de Catalunya, Barcelona, Spain

    Oscar Romero

  4. Poznań University of Technology, Poznan, Poland

    Robert Wrembel

  5. University of Paris-Saclay, Gif-sur-Yvette, France

    Francesca Bugiotti

  6. Free University of Bozen-Bolzano, Bozen-Bolzano, Italy

    Johann Gamper

  7. CNRS, Villeurbanne Cedex, France

    Genoveva Vargas Solar

  8. University of Calabria, Rende, Italy

    Ester Zumpano

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Bonomo, M., Ippolito, F., Morfea, S. (2023). A Knowledge Graph to Analyze Clinical Patient Data. In: Abelló, A., et al. New Trends in Database and Information Systems. ADBIS 2023. Communications in Computer and Information Science, vol 1850. Springer, Cham. https://doi.org/10.1007/978-3-031-42941-5_41

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  • DOI: https://doi.org/10.1007/978-3-031-42941-5_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-42940-8

  • Online ISBN: 978-3-031-42941-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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