Impact of Reflexive Ontologies in Semantic Clinical Decision Support Systems
Egileak: Arkaitz Artetxe, Eider Sánchez, Carlos Toro, Cesar Sanín, Edward Szczerbicki, Manuel Graña, Jorge Posada
Data: 05.03.2013
Cybernetics and Systems
Abstract
Ontology processing is arguably a time-consuming process with high associated computational costs. Query actions constitute a crucial part of the reasoning process and are a primary source of time consumption. Reflexive ontologies (ROs) is a novel approach intended to reduce time consumption problems while providing a fast reaction from ontology-based applications. In this article we present the implementation of a knowledge-based clinical decision support system (CDSS) for the diagnosis of Alzheimer's disease, which was the benchmark used to evaluate the impact of RO in the overall performance of the system. The implementation details and the definition of the implementation methodology are exposed in this article, along with the results of the evaluation. Some novel techniques that aim to optimize the performance of ROs are also presented with highlights of the test application introduced in our previous work.
BIB_text
author = {Arkaitz Artetxe, Eider Sánchez, Carlos Toro, Cesar Sanín, Edward Szczerbicki, Manuel Graña, Jorge Posada},
title = {Impact of Reflexive Ontologies in Semantic Clinical Decision Support Systems},
journal = {Cybernetics and Systems},
pages = {187-203},
number = {2},
volume = {44},
keywds = {
CDSS, clinical decision support system, knowledge engineering, reflexive ontologies
}
abstract = {
Ontology processing is arguably a time-consuming process with high associated computational costs. Query actions constitute a crucial part of the reasoning process and are a primary source of time consumption. Reflexive ontologies (ROs) is a novel approach intended to reduce time consumption problems while providing a fast reaction from ontology-based applications. In this article we present the implementation of a knowledge-based clinical decision support system (CDSS) for the diagnosis of Alzheimer's disease, which was the benchmark used to evaluate the impact of RO in the overall performance of the system. The implementation details and the definition of the implementation methodology are exposed in this article, along with the results of the evaluation. Some novel techniques that aim to optimize the performance of ROs are also presented with highlights of the test application introduced in our previous work.
}
isi = {1},
date = {2013-03-05},
year = {2013},
}
