Paper Info
Title
Knowledge Discovery and Risk Prediction for Chronic Diseases: An Integrated Approach.
Abstract
A novel ontology based type 2 diabetes 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
2011
10.1007/978-3-642-23957-1_31
IFIP Advances in Information and Communication Technology
Keywords
Field
DocType
Knowledge discovery,knowledge representation,chronic disease ontology,personalized risk evaluation system
Data science,Transduction (machine learning),Ontology,Ontology-based data integration,Knowledge representation and reasoning,Risk analysis (business),Computer science,Expert system,Decision support system,Knowledge extraction
Conference
Volume
ISSN
Citations 
363
1868-4238
0
PageRank 
References 
Authors
0.34
11
5
Name
Order
Citations
PageRank
Anju Verma1192.70
Maurizio Fiasché2499.23
Maria Cuzzola3194.12
Francesco Carlo Morabito433954.83
Giuseppe Irrera551.61