#वैAIद

Abstract - In recent years, nearly one death has occurred every minute because of heart-related diseases. With advancement in lifestyle, there is high amount of fast food eaten in today generation leading to high cholesterol level in the body. With help of the Data science and machine learning we can have a huge impact on healthcare industry. It is quite crucial to predict these diseases beforehand, so the patient can go through diagnosis for the same.Using machine learning we would automate the process of heart disease prediction using the medical history and several other factor. We would use the existing database on such topic to train our model and make it effective in nature using algorithms using supervised learning such as Random Forest, Decision Tree, and unsupervised learning Neural network etc., to predict the likelihood of heart disease and classify patients' risk level. As a result, the final machine learning model will be decided after observing the performance of various specified classification algorithms. This system would help in enhancing the medical care and making the medical care cost effective and could be instrument help for user.

Introduction - Heart disease is a major cause of death globally, it is the top most cause of death in the whole world. According to WHO, more than 17.5 million people lost their lives from heart diseases in 2016, accounting for around 1/3rd of all fatalities across the world. There are several projectsrelated to this topic online, about similar interest. Several of the effective predictor has been made using various supervised and unsupervised learning such as KNN, random forest, Neural and etc. Each of which has its own strength and weaknesses. Nearly 805000 Americans have a heart attack every year according to the data of 2019. Among all the heart diseases, coronary heart disease which is deadly among all the heart disorders. We know that heart attacks can be avoided easily and some modest lifestyle changes and quitting smoking, eating healthier and exercising regularly can help us in avoiding these fatal heart diseases. So, it is high time to examine and prevent the death rate by rightly guessing the disease in its beginning stages itself. In the modern world, with the use of machine learning and AI in medicine field, the opportunities to prosper are truly great. Artificial intelligence and machine learning in medicine has proven to be a boon to mankind. With the use of AI, examination and diagnosis of diseases has become a less challenging task. AI and machine learning can be used throughout complicated treatments and operations. In our Machine learning model, the major attributes on which we are going to work upon age ,gender of person, chest pain type, maximum heart rate, cholesterol and many other features are used. Our Target Variable will produce a binary output, binary:1 means “There is a risk”, binary:0 “There is no risk”.

RELATED WORK - Basically, we plan to create a project that could help a person to predict whether he has risk of getting heart related disease or not, using basic simple input parameter which would help the person to get expert help and advice on the same which would be instrumental for the person wellbeing. The risk of coronary heart disease is identified using McPherson, which uses unsupervised learning algorithm, Neural networks using it for the prediction for the model to be accurate and efficient in nature. Other similar work in this field is Diagnosis and prediction of heart disease and blood pressure with aid of neural network was introduced by R. Subramaniam, which include hundreds of hidden layers, which is one of the layman ways of predicting precise and accurate result. We look to explore and the current option and the option that could be added at the time using the knowledge of the existing and add some changes to enhance the model further.