Extensive Analysis of Machine Learning Techniques in the Field of Heart Disease

CAD (Coronary Artery Diseases) and CHF (Chronic Heart Failure) are two main forms of heart disease that lead to heart attacks. This disease is increasing the number of casualties worldwide. The heart is an organ that circulates filtered blood to each part of the body. The normal working of the heart is affected due to various conditions like Obesity, Hypertension, lifestyle etc. The large volume of heart diseases is avertable, but they continue to increase for the reason that protective measures are insufficient. To cure these life-threatening diseases, we need a more reliable and accurate system. Machine learning procedures have been employed on numerous therapeutic datasets to industrialise the investigation of medical data. Recently, many researchers have started applying a number of machine learning techniques to assist the medical community and experts in the detection of heart-related issues.Classification technique like Support Vector Machine,Artificial Neural Network and Random Forest are examples of data mining and machine learning approaches that are used to forecast heart disorders. This can help clinician to decide on the diagnosis and forecast of cardiac illness. The prime intention behind writing this research paper is to use machine learning procedures to forecast a patient's heart condition.