Context-aware for predicting gestational diabetes using rule – based system

Abstract Nanotechnology seems to be an important scientific method for the diagnosis of a disorder that offers more precise and appropriate health information. Diabetes mellitus (DM) is a chronic condition frequently seen that severely affects human health. Gestational diabetes happens during gestation or gestational time. Gestational diabetes may arise from normal physical changes in the body experiences of a pregnant woman.. The placenta develops substances during pregnancy that conflict with just the enzyme insulin’s behavior. The Principle objective of this paper is to predict gestational diabetes using the rule-based system by creating a user profile with AbA1c. This research can be applied to a broader range of healthcare diagnostics to get better accuracy in the prediction