Heart Disease Prediction Using KNN

Abstract

The purpose of this project is to build a strong machine-learning model to predict heart disease with high accuracy by taking input parameters related to weight, height, and many other important health metrics of a patient. Heart diseases are a leading cause of death and kill almost 17.6 million people every year. Such harrowing numbers indicate the necessity for actionable early detection and prevention measures. This model leverages on K -Nearest Neighbors (KNN) machine learning algorithm which classifies patients based on their risks of suffering from a heart disease. This model developed an impressive accuracy of 91%, making it a valuable tool for doctors. This particular model can help early identification of heart disease, which can be significant in saving the lives of millions of patients.