During the recent global urgency, scientists, clinicians, and healthcare experts around the globe keep on searching for a new technology to support in tackling the Covid-19 pandemic. The evidence of Machine Learning and Artificial Intelligence application on the previous epidemic encourage researchers by giving a new angle to fight against the novel Coronavirus outbreak. Making risk-free surroundings will be priority of every person's mind so that life can be conductive just as before. Diabetes is an around the world predominant infection that can cause obvious micro vascular confusions like diabetic retinopathy macular edema in the natural eye retina, Cardiovascular, TB, Nephrology, Parkinson disease. In modern medical science, images are basic instrument for exact information of patients. Meanwhile assessment of contemporary clinical symbolisms stays complex. This disease data can predominant in various ways to cause of death rate factors. We collected different types of disease with comorbidity of diabetes along with other disease dearth rate dataset is collected from Kaggle and PubMed source. Using machine learning and Deep learning concept we are classify the images of chest x-rays and CT scan images of eyes, Lungs, which can effect of various disease symptoms along effect of organs also. Here majorly focused on Coronavirus, Diabetes Mellitus, TB, Kidney disease images ete.. Using Artificial Neural Network and KNN can classify the images and LR and Random forest algorithms created plots of images how fast its grown up and getting accuracy of various disease risk factors like 72-85% Diabetes to Retinopathy, 75-85% TB, Diabetes to Nephrology 75-92%, Covid-19 to TB is 80-95% and Covid-19 to Alzheimer’s 80-90%, Covid-19 to Diabetes 80-95%. This factor of accuracy is calculated based on WHO record and radiologist’s suggestion.