Blood Sugar Prediction with an Improved Mechanism for Diabetic using Recurrent Neural Networks

Abstract

In the Current 2020 Covid-19 Situation, less expensive sensors measuring sugar levels in continuous intervals are essential. These, combined with easily usable devices plugged with SAAS based Deep Learning Solutions, allow for customized health and disease management grades. Deep Learning Systems scalable technologies are allowed by sensors, analytical tasks, and people. This brings us to the question of volume for creating such DL Solutions, which we can present for the current situation of the COVID-19 pandemic. The technique is based on scratch-trained RNN, requiring the amount of sugar of a patient in graded detail. The model predicts and estimates sugar and possible health issues accurately. There is no need for a reduction in this pre-processing system and function, which saves the calculation.