(untitled) (International Journal of Food and Nutritional Sciences, 2022)
Heart disease is one of the most significant reasons of mortality in the current days. Now days it is very complicated task to predict the cardiovascular disease in the area of clinical data analysis. All the prediction is done by using manual approach which is becoming time complexity for the end users to find out the abnormalities. Hence this motivated me to designthe proposed application in order to efficient heart disease prediction using machine learning (ML) algorithm. In current days ML has been shown to be effective in assisting in making decisions and predictions from the large quantity of data produced by the healthcare industry. This is mainly because of its usage in different areas especially in the medical field. In this proposed work, we propose a novel model which is specifically that aims at finding significant features by applying machine learning techniques resulting in improving the accuracy in the prediction of cardiovascular disease. This proposed application is trained by using several ML algorithms and then check the following factors such as accuracy, precision, recall and F1- Score.By conducting various experiments on several ML Algorithms by taking UCI dataset, we finally check which algorithm fits best for efficient heart disease prediction.