An Integrated Approach for Ontology Based Personalized Modeling

Populations are aging and prevalence of chronic diseases, persisting for many years,is increasing. Chronic diseases such as CVD, T2DM and obesity have high prevalence and develop over the course of life due to a number of interrelated factors including genetic predisposition, nutrition and lifestyle. A computerized model focused on organizing knowledge related to genes, nutrition and three chronic diseases, CVD, T2DM and obesity has been developed for the Ontology-Based Personalized Risk Evaluation for Chronic Disease Project. This model facilitates to identify interrelationships between concepts. One method, called transductive neuro-fuzzy inference system with weighted data normalization (Song and Kasabov, 2007)has been used to evaluate personalized risk of chronic diseases. A framework to integrate the personalized model and the chronic disease ontology has been developed with the aim of providing support for further discovery through the integration of the ontological representation in order to build an expert system in genes of interest and relevant dietary components.

Autorentext

Dr Anju Verma has developed a novel ontology for three chronic diseases and its integration with local and personalized modeling techniques which involve different statistical and neuro-fuzzy methods. Her research interests are mainly to find interactions among genes of different chronic diseases. To contact Dr Verma email on a05verma@yahoo.com