Extended Reflexive Ontologies for the Generation of Clinical Recommendations

Eider Sanchez; Carlos Toro; Manuel Graña; Cesar Sanin; Edward Szczerbicki

doi:10.1080/01969722.2015.1007723

Extended Reflexive Ontologies for the Generation of Clinical Recommendations

Abstract

Decision recommendations are a set of alternative options for clinical decisions (e.g., diagnosis, prognosis, treatment selection, follow-up, and prevention) that are provided to decision makers by knowledge-based Clinical Decision Support Systems (k-CDSS) as aids. We propose to follow a ‘‘reasoning over domain’’ approach for the generation of decision recommendations by gathering and inferring conclusions from production rules. In order to rationalize our approach, we present a specification that will sustain the logic models supported in the knowledge bases we use for persistence. We introduce first the underlying knowledge model and then the necessary extensions that will convey toward the solution of the reported needs. The starting point of our approach is the proposition of Reflexive Ontologies (RO). Here, we go a step further, proposing an extension of RO that includes the handling and reasoning that production rules provide. Our approach speeds up the recommendation generation process.

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Authors (5)

Eider Sanchez
- University of The Basque Country UPV/EHU .
Carlos Toro
- VicomTech Research Institute .
Manuel Graña
- University of The Basque Country UPV/EHU .
Cesar Sanin
- University of Newcastle School of Engineering
Edward Szczerbicki prof. dr hab. inż.

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Category:: Articles
Type:: artykuł w czasopiśmie wyróżnionym w JCR
Published in:: CYBERNETICS AND SYSTEMS no. 46, edition 1-2, pages 4 - 18,
ISSN: 0196-9722
Language:: English
Publication year:: 2015
Bibliographic description:: Sanchez E., Toro C., Graña M., Sanin C., Szczerbicki E.: Extended Reflexive Ontologies for the Generation of Clinical Recommendations// CYBERNETICS AND SYSTEMS. -Vol. 46, iss. 1-2 (2015), s.4-18
DOI:: Digital Object Identifier (open in new tab) 10.1080/01969722.2015.1007723
Verified by:: Gdańsk University of Technology