Title :
A fuzzy-based ontology for Alzheimer´s disease decision support
Author :
Firas Zekri;Rafik Bouaziz;Emna Turki
Author_Institution :
MIR@CL Laboratory, University of Sfax, Faculty of Economics and Management, Airport Road 4 km, B.P. 1088, 3018., Tunisia
Abstract :
The fight against Alzheimer´s disease (AD) has become a major issue. We aim to contribute to this fight by seeking to provide adequate software to assist decision makers in the field of AD to choose the optimal decision for each situation. Moreover, it is now recognized that fuzzy ontologies are useful tools for the representation of crisp and fuzzy knowledge and reasoning on it. Thus, we propose in this paper a fuzzy ontology called “AlzFuzzyOnto”, related to the AD concepts. This ontology enables semantic representation of medical data for diagnosis and support of AD, while taking into account the uncertainties and inaccuracies associated with this disease. To this end, we used the Mind ontology, as initial core ontology, in the building process of the ontology “AlzFuzzyOnto”, which we have standardized to facilitate the integration of rule bases.
Keywords :
"Ontologies","Alzheimer´s disease","Medical diagnostic imaging","Semantics","Medical treatment","Uncertainty"
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2015 IEEE International Conference on
DOI :
10.1109/FUZZ-IEEE.2015.7337922