Prediction Techniques of Heart Disease and Diabetes Disease using Machine Learning

Abstract

Heart disease and Diabetes disease is one of the most common diseases. These diseases are quite common nowadays so we used different attributes which can relate to these diseases well to find the better method to predict and we also used algorithms for prediction. Generally, People in IT sectors are becoming stressed due to their busy schedules and targets. So, they don't have sufficient time to take care of their health and families. To overcome this, we have created a website named MEDCARE to collect the sensor data and to produce the result. Notwithstanding this weight is the serious issue which is making a significant effect in everybody's life. So that in this web application they can likewise see their wellbeing status by weight list (Body Mass Index). Random Forest Classifier and K Nearest Neighbour, algorithm is analyzed on data set based on risk factors. Here the trained data sets and incoming test cases are processed by a machine learning algorithm and produce the results accordingly. Perform enlightening examination on heart disease illness forecast, bosom malignancy expectation and diabetes forecast utilizing key components like Glucose levels, Blood Pressure, Skin Thickness, BMI and so forth Outwardly investigate these factors, you may have to search for the dissemination of these factors utilizing histograms. On the off chance that they neglect to screen their health status the application will inform the employee to deal with their health.