Speed-up of a Knowledge-Based Clinical Diagnosis System using Reflexive Ontologies

@Article {
author = {Arkaitz Artetxe and Eider Sanchez and Carlos Toro and Cesar Sanín and Edward Szczerbicki and Manuel Graña and Jorge Posada},
title = {Speed-up of a Knowledge-Based Clinical Diagnosis System using Reflexive Ontologies},
pages = {1480-1489},
volume = {243},
keywds = {

Knowledge Engineering, Reflexive Ontologies, Evaluation, Knowledge-Based System

}
abstract = {

Most of the time expended during ontology processing is derived from query actions. Quasi-real time goals require new approaches towards time efficiency (e.g. an intensively consumed application that pulls knowledge from an ontology). Reflexive Ontologies are a recent approach that is intended to bridge some of the aforementioned time consumption issues. In this paper we present an implementation of the Reflexive Ontologies in a knowledge-based Clinical Decision Support System for the diagnosis of Alz-heimer’s Disease. Our implementation is evaluated in order to show the impact of the application of reflexivity in the context described above. We give implementation details, as well as the definition of the evaluation methodology and evaluation results. Lastly performance improvements and some highlights of the application are also discussed.

}
isbn = {978-1-61499-105-2},
isi = {1},
date = {2012-09-10},
year = {2012},
}