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A Comparative Analysis of the Completeness and Concordance of Data Sources with Cancer-Associated Information

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Advances in Conceptual Modeling (ER 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13650))

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Abstract

Precision medicine promises to improve the diagnosis and treatment of patients based on their genetic particularities. One of the fields in which clinicians aim to use precision medicine is oncology. The knowledge that is necessary to achieve a proper precision oncology application is dispersed over many data sources with heterogeneous data representations. In this work, we studied seven of the most relevant data sources used to deliver precision oncology and determined if the information contained in them is complete and concordant. The results herein reported indicate that this information is neither complete nor concordant. Thus, providing proper precision oncology is still an unresolved challenge for clinicians.

Supported by ACIF/2021/117, MICIN/AEI/10.13039/501100011033, and INNEST/2021/57 grants.

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Notes

  1. 1.

    Through grant INNEST/2021/57.

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Authors and Affiliations

  1. PROS Group, Valencian Research Institute (VRAIN), Universitat Politècnica de València, Camí de Vera, s/n, 46022, València, Spain

    Mireia Costa, Alberto García S. & Oscar Pastor

Authors
  1. Mireia Costa
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  2. Alberto García S.
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  3. Oscar Pastor
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Corresponding author

Correspondence to Mireia Costa .

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Editors and Affiliations

  1. University of Twente, Enschede, The Netherlands

    Renata Guizzardi

  2. Johannes Kepler University Linz, Linz, Austria

    Bernd Neumayr

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Costa, M., García S., A., Pastor, O. (2022). A Comparative Analysis of the Completeness and Concordance of Data Sources with Cancer-Associated Information. In: Guizzardi, R., Neumayr, B. (eds) Advances in Conceptual Modeling. ER 2022. Lecture Notes in Computer Science, vol 13650. Springer, Cham. https://doi.org/10.1007/978-3-031-22036-4_4

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  • DOI: https://doi.org/10.1007/978-3-031-22036-4_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-22035-7

  • Online ISBN: 978-3-031-22036-4

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