Title :
Bayesian approach for minimizing nephropathy risk for patients with type 2 diabetes
Author :
Fellaji, Soumaya ; Azmani, Abdellah ; Akharif, Abdelhadi
Author_Institution :
Fac. of Sci. & Technol., Lab. of Math. & Applic., Abdelmalek Essaadi Univ., Tangier, Morocco
Abstract :
This paper presents the application of an approach based on the Bayesian Networks technique to minimize nephropathy risk in type 2 diabetics. This model consists to assess risk factors of type 2 diabetes and nephropathy by using prevalence extracted from the World Health Organization statistics and the health status report of Moroccan population of 2012. This prevalence has helped to test the validity of the proposed model and to develop relationships between various factors. This approach has shown the influence of different risk factors and the role of lifestyle modification to minimize nephropathy risk.
Keywords :
Bayes methods; belief networks; diseases; health care; medical computing; risk management; Bayesian approach; Bayesian networks technique; Moroccan population; World Health Organization statistics; health status report; lifestyle modification; nephropathy risk minimization; probabilistic graphical models; risk factors; type 2 diabetes; Diabetes; Genetics; Hypertension; Lead; Obesity; Bayesian Networks; Nephropathy; Type 2 Diabetes;
Conference_Titel :
Intelligent Systems: Theories and Applications (SITA-14), 2014 9th International Conference on
Conference_Location :
Rabat
Print_ISBN :
978-1-4799-3566-6
DOI :
10.1109/SITA.2014.6847311
