A Rule-Based Monitoring System for Accurate Prediction of Diabetes

Yugal Kumar, Anand Srivastava, Pradeep Singh

OAI: oai:igi-global.com:251855 • DOI: 10.4018/IJEHMC.2020070103

Diabetes is a chronic disease that can affect the life of people due to high sugar level in their blood. The sugar level is increased due to a lack of production of insulin in the human body. Large numbers of people are affected with diabetes and it can increase tremendously due life style behavior. Diabetes can also affect the other human organs, like kidneys, hearts, retinas and lead to the failure of these organs. This article presents a diabetic monitoring system to determine the risk of diabetes based on the personal health record of patients. In this work, several rules are designed based on the clinical as well as non-clinical symptoms. The effectiveness of the diabetes monitoring system is tested on a set of two hundred forty people. The simulation results are also compared with well-known techniques available for diabetes prediction. It is stated that proposed monitoring system obtains 90.41% accuracy rate as compared with other techniques.

Health Information Systems Medical, Healthcare, and Life Sciences Health Information Systems