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  • Representing and querying now-relative relational medical data

    Author(s)
    Anselma, Luca
    Piovesan, Luca
    Stantic, Bela
    Terenziani, Paolo
    Griffith University Author(s)
    Stantic, Bela
    Year published
    2018
    Metadata
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    Abstract
    Temporal information plays a crucial role in medicine. Patients’ clinical records are intrinsically temporal. Thus, in Medical Informatics there is an increasing need to store, support and query temporal data (particularly in relational databases), in order, for instance, to supplement decision-support systems. In this paper, we show that current approaches to relational data have remarkable limitations in the treatment of “now-relative” data (i.e., data holding true at the current time). This can severely compromise their applicability in general, and specifically in the medical context, where “now-relative” data are essential ...
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    Temporal information plays a crucial role in medicine. Patients’ clinical records are intrinsically temporal. Thus, in Medical Informatics there is an increasing need to store, support and query temporal data (particularly in relational databases), in order, for instance, to supplement decision-support systems. In this paper, we show that current approaches to relational data have remarkable limitations in the treatment of “now-relative” data (i.e., data holding true at the current time). This can severely compromise their applicability in general, and specifically in the medical context, where “now-relative” data are essential to assess the current status of the patients. We propose a theoretically grounded and application-independent relational approach to cope with now-relative data (which can be paired, e.g., with different decision support systems) overcoming such limitations. We propose a new temporal relational representation, which is the first relational model coping with the temporal indeterminacy intrinsic in now-relative data. We also propose new temporal algebraic operators to query them, supporting the distinction between possible and necessary time, and Allen’s temporal relations between data. We exemplify the impact of our approach, and study the theoretical and computational properties of the new representation and algebra.
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    Journal Title
    Artificial Intelligence in Medicine
    Volume
    86
    DOI
    https://doi.org/10.1016/j.artmed.2018.01.004
    Subject
    Engineering
    Publication URI
    http://hdl.handle.net/10072/379838
    Collection
    • Journal articles

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