Open AccessPrediction of Heart Disease Using Machine Learning
Author(s) -
M. Prasanna,
Shrijith Shetty P,
K Mamatha
Publication year - 2021
Publication title -
international journal of scientific research in computer science, engineering and information technology
Language(s) - English
Resource type - Journals
ISSN - 2456-3307
DOI - 10.32628/cseit217355
Subject(s) - decision tree , machine learning , computer science , artificial intelligence , heart disease , disease , blood pressure , medicine , cardiology
Heart disease is one of the most significant causes of mortality in the world today. Prediction of Heart disease is a critical challenge in the area of clinical data analysis. Machine learning has been shown to be effective in assisting in making decision and predictions from large quantity of data produced by the health industry. Several types of heart diseases are expanding day by day because of way of life, genetic problem, blood pressure, cholesterol level, pulse rate etc. So the diagnose of disease plays important role for the prevention of heart related problems. Researchers received different methods to analyze it. This system aims at Predicting heart disease with various machine learning techniques and increasing the accuracy of the system. Classification approach consists of two algorithms such as KNN classification algorithm and Decision tree algorithm. The result of classification shows 86% accuracy by using n number of neighbors in this approach.