Efficient diagnostic system for smart diabetes

Abstract

5G networks, analytics of medical data and the internet of things are recent advances in big data technologies. Combining these advances with wearable computing and artificial intelligence, innovative diabetics monitoring system is implemented. In the existing system, it classifies the Diabetes 1.0 and Diabetes 2.0 methods, which show the intelligence and networking deficiencies. Thus, with personalized treatment, our goal is to design a sustainable, cost-effective, and smart diabetes diagnosis solution. Uses the machine learning algorithms in the proposed 5G smart diabetes-Naive Bayes, Logistic regression and artificial neural networks (ANN) are for the results.