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Considering Temporal Preferences and Probabilities in Guideline Interaction Analysis

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Artificial Intelligence in Medicine (AIME 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11526))

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Abstract

The treatment of patients affected by multiple diseases (comorbid patients) is one of the main challenges of the modern healthcare, involving the analysis of the interactions of the guidelines for the specific diseases. Practically speaking, such interactions occur in time. The GLARE project explicitly provides temporal representation and temporal reasoning methodologies to cope with such a fundamental issue. In this paper, we propose a further improvement, to take into account that, often, (i) the actions in the guidelines can be executed by physicians at different times with different preferences, and that (ii) the effects of such actions have a probabilistic distribution in time. In our approach, physicians may investigate what are the preferences of their choices on the execution-time of guideline actions, and the probabilities that their effects temporally intersect (interactions may occur only in case effects intersect in time).

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Authors and Affiliations

  1. DISIT, Institute of Computer Science, Università del Piemonte Orientale, Alessandria, Italy

    Paolo Terenziani

  2. ITCS Sommeiller, Corso Duca degli Abruzzi 20, 10129, Turin, Italy

    Antonella Andolina

Authors
  1. Paolo Terenziani
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  2. Antonella Andolina
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Corresponding author

Correspondence to Paolo Terenziani .

Editor information

Editors and Affiliations

  1. Universitat Rovira i Virgili, Tarragona, Spain

    David Riaño

  2. Poznan University of Technology, Poznan, Poland

    Szymon Wilk

  3. VU Amsterdam, Amsterdam, The Netherlands

    Annette ten Teije

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Terenziani, P., Andolina, A. (2019). Considering Temporal Preferences and Probabilities in Guideline Interaction Analysis. In: Riaño, D., Wilk, S., ten Teije, A. (eds) Artificial Intelligence in Medicine. AIME 2019. Lecture Notes in Computer Science(), vol 11526. Springer, Cham. https://doi.org/10.1007/978-3-030-21642-9_16

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  • DOI: https://doi.org/10.1007/978-3-030-21642-9_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-21641-2

  • Online ISBN: 978-3-030-21642-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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