Cardio Vascular Disease Prediction By Using Machine Learning Algorithms - Sunita Nandgave , Nahista Anjum Abuzar Ansari , Faheem Kasuar (International Journal of Advanced Science and Technology, 2020)
About 17.5 million passings from cardiovascular malady happen around the world. India at present has more than 30 million heart patients. The disposition of oblivious individuals towards wellbeing can prompt an assortment of maladies and can be perilous. In the medicinal services segment, a lot of information are regularly produced. Nonetheless, it is frequently not utilized viably. The information show that the picture, sound, message or created document have some concealed examples and their connections. The apparatuses used to extricate information from these databases for the clinical finding of infections or different reasons for existing are less normal. Obviously, on the off chance that you can make a component or framework that can convey your psyche to individuals and caution you dependent on your clinical history, it will be of extraordinary assistance. Flow exploratory examinations use machine learning (ML) to anticipate an individual’s coronary illness chance components, contingent upon the different attributes of clinical history. Methods have been applied to numerous clinical datasets to mechanize the examination of enormous and complex information. Techniques like machine learning, KNN, SVM, Random Forest, Decision Tree, ANN, Genetic Algorithms etc. A machine learning technique provides various services in health care industry to diagnose the problem of heart related diseases. Classification is among the most powerful technique of machine learning which is used for prediction of heart disease along with some algorithms which exhibit accuracy. The accuracy of various algorithms is measured and the algorithms are compared. The result of this experimental analysis is a 0 or 1 result which does not represent any danger for the individual. Django is used to manage a website. The proposed system, Heart Disease Prediction System with the help of Machine Learning Algorithms. Here the system is going to use Logistic regression, Naïve Bayes, Decision tree and SVM Algorithm to process the large scale data to predict Heart Disease