Specification of Extended Reflexive Ontologies in the context of CDSS

Egileak:

Data: 18.12.2014

Studies in health technology and informatics


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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 towards the solution of the reported needs. The starting point of our approach is the work of Toro et al. [13] on Reflexive Ontologies (RO). We also propose an extension of RO, by including the handling and reasoning that production rules provide. Our approach speeds-up the recommendation generation process.

BIB_text

@Article {
title = {Specification of Extended Reflexive Ontologies in the context of CDSS},
journal = {Studies in health technology and informatics},
pages = {234-243},
volume = {207},
keywds = {

Reflexive Ontologies, fast query system, rule engine, autopoiesis


}
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 towards the solution of the reported needs. The starting point of our approach is the work of Toro et al. [13] on Reflexive Ontologies (RO). We also propose an extension of RO, by including the handling and reasoning that production rules provide. Our approach speeds-up the recommendation generation process.


}
pubmed = {1},
date = {2014-12-18},
year = {2014},
}
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