Effective Prediction of Heart Disease Through Machine Learning

Abstract

In present times, in the field of healthcare, identification of heart disease is difficult. Just because of this heart disease, around one person passes away per minute in the modern era. There is a requirement of automation of prediction system to avoid hazard related with it as well as aware the patient’s health in advance. There are various ML techniques that have been exposed to be helpful in supporting predictions and making decisions from the huge data which is generated through the medical industries. In this article, we offer a new system that intends to focus on important features through concerning machine learning methods that result in improved accurateness within the heart disease prediction. The proposed model is established by special features combinations and numerous recognized classification methods. We generate an improved performance level through an above 80% accuracy level throughout the proposed model intended for heart disease prediction system by the hybrid model. Therefore, this article represents a relative learning by evaluating the performance of various machine learning techniques.