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  • Temporal conformance analysis and explanation on comorbid patients

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    TERENZIANI229848.pdf (274.9Kb)
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    Version of Record (VoR)
    Author(s)
    Piovesan, L
    Terenziani, P
    Dupré, DT
    Griffith University Author(s)
    Terenziani, Paolo
    Year published
    2018
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    Abstract
    The treatment of comorbid patients is one of the main challenges of modern health care, and many Medical Informatics approaches have been devoted to it in the last years. In this paper, we propose the first approach in the literature that analyses the conformance of execution traces with multiple Computer-Interpretable Guidelines (CIGs), as needed in the treatment of comorbid patients. This is a fundamental task, to support physicians in an a-posteriori analysis of the treatments that have been provided. Notably, the conformance problem is very complex in this context, since CIGs may have negative interactions, so that in ...
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    The treatment of comorbid patients is one of the main challenges of modern health care, and many Medical Informatics approaches have been devoted to it in the last years. In this paper, we propose the first approach in the literature that analyses the conformance of execution traces with multiple Computer-Interpretable Guidelines (CIGs), as needed in the treatment of comorbid patients. This is a fundamental task, to support physicians in an a-posteriori analysis of the treatments that have been provided. Notably, the conformance problem is very complex in this context, since CIGs may have negative interactions, so that in specific circumstances full conformance to individual CIGs may be dangerous for patients. We thus complement our conformance analysis with an explanation approach, aimed at justifying deviations in case they can be explained in terms of interaction management, e.g., some possible undesired interaction has been avoided. Our approach is based on Answer Set Programming, and, to face realistic problems, devotes specific attention to the temporal dimension.
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    Conference Title
    HEALTHINF 2018 - 11th International Conference on Health Informatics, Proceedings; Part of 11th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2018
    Volume
    5
    DOI
    https://doi.org/10.5220/0006535400170026
    Copyright Statement
    © 2018 SciTePress. The attached file is reproduced here in accordance with the copyright policy of the publisher. Please refer to the conference's website for access to the definitive, published version.
    Subject
    Artificial intelligence
    Publication URI
    http://hdl.handle.net/10072/385810
    Collection
    • Conference outputs

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