Existential Risk Prediction Models for Diabetes Mellitus

Diabetes mellitus is a disease of the human body that caused by high blood sugar levels and inactivity, poor eating habits, being overweight etc. This paper reviewed, analyzed diabetes Type 1, 2, Gestational diverse risk prediction models algorithms employed. In this study, methodology adopted exploratory descriptive approach, which clearly describes various deep learning machine model used for classification forecasting problems. The Deep Neural Network Model given in work have highest score terms accuracy outperformed performance, there also issue other algorithms' precision. It recommended when conducting survey on different variants mellitus, researchers consider using explicitly described while paying close attention to their advantages disadvantages, as well potential outcomes. possible combine techniques create ensemble models, can improve performance.