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Guideline Formalization and Knowledge Representation for Clinical Decision Support

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Author(s): Tiago OLIVEIRA | José NEVES | Paulo NOVAIS

Journal: ADCAIJ : Advances in Distributed Computing and Artificial Intelligence Journal
ISSN 2255-2863

Volume: 1;
Issue: 2;
Start page: 1;
Date: 2013;
Original page

Keywords: Computer-Interpretable | Guidelines | Incomplete Information | Quality of Information | Decision Support

ABSTRACT
The prevalence of situations of medical error and defensive medicine in healthcare institutions is a great concern of the medical community. Clinical Practice Guidelines are regarded by most researchers as a way to mitigate these occurrences; however, there is a need to make them interactive, easier to update and to deploy. This paper provides a model for Computer-Interpretable Guidelines based on the generic tasks of the clinical process, devised to be included in the framework of a Clinical Decision Support System. Aiming to represent medical recommendations in a simple and intuitive way. Hence, this work proposes a knowledge representation formalism that uses an Extension to Logic Programming to handle incomplete information. This model is used to represent different cases of missing, conflicting and inexact information with the aid of a method to quantify its quality. The integration of the guideline model with the knowledge representation formalism yields a clinical decision model that relies on the development of multiple information scenarios and the exploration of different clinical hypotheses.
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