Providing sustainable living through early detection of metabolic syndrome

The non-healthy lifestyle of the people in developed countries is one of the reasons for higher amounts of atherosclerosis and diabetes type 2, which are related to a metabolic syndrome. This paper proposes an intelligent system for the early, unobtrusive detection of metabolic syndrome in order to support sustainable environments for today’s and tomorrow’s generations. An implementation of Fuzzy ARTMAP Neural Network for diagnosis of Metabolic Syndrome is presented. It allows classifying H NMR serum spectra into five classes, from healthy person to person with Metabolic Syndrome. Using “Voting strategy†it gains an ability to classify samples with a confidence value