1. VADTHE NARASIMHA - JNTUH Research Scholar, Department of Computer Science and Engineering, CMR College of
Engineering & Technology, Hyderabad, Telangana-501401, India.
2. Dr. M. DHANALAKSHMI - Professor of Information Technology, JNTUH Jagityala, Hyderabad, Telangana-505501, India.
SARS_Cov2 know everyone now a day due to its effects not only healths also economically and at the movement pandemic of all the time in lockdown most of the diabetes patients are suffer with COVID-19. Across the world 30% to 60% of diabetes patients suffered with COVID-19 with various regions, so diabetic patients have more mortality because COVID-19 virus is to effect on sever acute respiratory syndrome in that scenario lungs can damage more. Some diabetic patients have balance glycemic profile during corona virus outbreak. In this paper discussed on the outstanding of COVID-19 and diabetes patient’s historical data that can implemented using machine learning model with 98% of result using Random forest and XGBoost algorithm and dataset downloaded from kaggle. Here we are cross validated data with chest x-ray image and historical data of patients 1628 members information with good accuracy. Machine learning techniques are used for implementation of risk factor identification and cross validation of dataset.
SARS-COV2, Diabetes, Machine Learning, LR, Decision Tree, XGBoost.