Predicting Early Phase of Type 2 Diabetic by Deep Learning

Deep Neural Network with prediction is the one of the main deep learning technologies which has been used by many researches for early prediction of Type 2 Diabetics (T2D). For the prediction of the T2D, the taxonomy with the components are proposed with Data, Prediction processing and Display (DPD). Those components are evaluated for the better performance of the system and are validated with the different parameters for the early diagnosis of the T2D. The system being proposed has the higher accuracy for the prediction of the T2D and early detection of the diabetics in different age group in comparison to research paper reviewed and with current findings. It also helps to diagnose the diabetics in the patients. The critical analysis of the literature review of the latest published research paper available on the T2D and on deep learning has better accuracy for the prediction of T2D. On basis of the analysis, an effective system for T2D based on Deep Neural Network (DNN) has been developed in the system that can predict the diabetics in the early stage.