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A Modal Representation of Graded Medical Statements

  • Hans-Ulrich KriegerEmail author
  • Stefan Schulz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9804)

Abstract

Medical natural language statements uttered by physicians are usually graded, i.e., are associated with a degree of uncertainty about the validity of a medical assessment. This uncertainty is often expressed through specific verbs, adverbs, or adjectives in natural language. In this paper, we look into a representation of such graded statements by presenting a simple non-normal modal logic which comes with a set of modal operators, directly associated with the words indicating the uncertainty and interpreted through confidence intervals in the model theory. We complement the model theory by a set of RDFS-/OWL 2 RL-like entailment (if-then) rules, acting on the syntactic representation of modalized statements. Our interest in such a formalization is related to the use of OWL as the de facto standard in (medical) ontologies today and its weakness to represent and reason about assertional knowledge that is uncertain or that changes over time. The approach is not restricted to medical statements, but is applicable to other graded statements as well.

Keywords

Modal Logic Description Logic Propositional Formula Satisfaction Relation Propositional Letter 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

The research described in this paper has been co-funded by the Horizon 2020 Framework Programme of the European Union within the project PAL (Personal Assistant for healthy Lifestyle) under Grant agreement no. 643783. The authors have profited from discussions with our colleagues Miroslav Janíček and Bernd Kiefer and would like to thank the three reviewers for their suggestions.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.German Research Center for Artificial Intelligence (DFKI)SaarbrückenGermany
  2. 2.Institute of Medical InformaticsMedical University of GrazGrazAustria

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