Paper Info
Title
Ontology Based Personalized Modeling for Chronic Disease Risk Analysis: An Integrated Approach
Abstract
A novel ontology based chronic disease risk analysis system framework is described, which allows the creation of global knowledge representation (ontology) and personalized modeling for a decision support system. A computerized model focusing on organizing knowledge related to three chronic diseases and genes has been developed in an ontological representation that is able to identify interrelationships for the ontology-based personalized risk evaluation for chronic diseases. The personalized modeling is a process of model creation for a single person, based on their personal data and the information available in the ontology. A transductive neuro-fuzzy inference system with weighted data normalization is used to evaluate personalized risk for chronic disease. This approach aims to provide support for further discovery through the integration of the ontological representation to build an expert system in order to pinpoint genes of interest and relevant diet components.
Year
DOI
Venue
2009
10.1007/978-3-642-02490-0_146
Austr. J. Intelligent Information Processing Systems
Keywords
Field
DocType
chronic disease,system framework,expert system,decision support system,ontology-based personalized risk evaluation,integrated approach,ontological representation,personalized modeling,transductive neuro-fuzzy inference system,personalized risk,chronic disease risk analysis,risk analysis,knowledge representation
Transduction (machine learning),Data science,Ontology,Ontology-based data integration,Knowledge representation and reasoning,Computer science,Risk analysis (business),Expert system,Decision support system,Database normalization
Journal
Volume
Issue
ISSN
10
3
0302-9743
ISBN
Citations 
PageRank 
3-642-02489-0
4
0.41
References 
Authors
3
4
Name
Order
Citations
PageRank
Anju Verma1192.70
Nikola K Kasabov23645290.73
Elaine Rush340.41
Qun Song452229.25