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A Conceptual Model for Detecting Interactions among Medical Recommendations in Clinical Guidelines

A Case-Study on Multimorbidity

  • Conference paper
Knowledge Engineering and Knowledge Management (EKAW 2014)

Abstract

Representation of clinical knowledge is still an open research topic. In particular, classical languages designed for representing clinical guidelines, which were meant for producing diagnostic and treatment plans, present limitations such as for re-using, combining, and reasoning over existing knowledge. In this paper, we address such limitations by proposing an extension of the TMR conceptual model to represent clinical guidelines that allows re-using and combining knowledge from several guidelines to be applied to patients with multimorbidities. We provide means to (semi)automatically detect interactions among recommendations that require some attention from experts, such as recommending more than once the same drug. We evaluate the model by applying it to a realistic case study involving 3 diseases (Osteoarthritis, Hypertension and Diabetes) and compare the results with two other existing methods.

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Zamborlini, V., Hoekstra, R., da Silveira, M., Pruski, C., ten Teije, A., van Harmelen, F. (2014). A Conceptual Model for Detecting Interactions among Medical Recommendations in Clinical Guidelines. In: Janowicz, K., Schlobach, S., Lambrix, P., Hyvönen, E. (eds) Knowledge Engineering and Knowledge Management. EKAW 2014. Lecture Notes in Computer Science(), vol 8876. Springer, Cham. https://doi.org/10.1007/978-3-319-13704-9_44

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  • DOI: https://doi.org/10.1007/978-3-319-13704-9_44

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-13703-2

  • Online ISBN: 978-3-319-13704-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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