Predictive analytics on Covid using recurrent neural network

In this paper, we develop a risk based predictive analytics model utilizing the available dataset to train the model. To predict the likelihood of a new strain of Covid-19 syndrome in patients, the researchers used a deep learning classifier called Recurrent Neural Network (RNN). The study considers diabetes patients as the respondents and the data is collected from the diabetes patients. The risk of covid-19 effects on diabetes patients are deeply analyzed using RNN. The collected datasets are initially pre-processed and then the features are extracted with final classification using RNN. The experimental analysis is conducted to validate the efficacy of the predictive analytics using RNN. The findings indicate that the suggested RNN outperforms other approaches for forecasting covid-19 risk in diabetic patients.