A Review on Heart Disease Monitoring System by Using Machine Learning
Abstract
Heart disease is one of the most popular diseases which can lead to reduce the lifespan of human beings now a day. Every year 17.5 million people are get dying due to heart disease. Researchers have been using various types of data mining techniques and machine learning algorithms to help in the diagnosis of heart disease and various other type of diseases. Health care Centre collects large amount of data. Data mining is the process of discovering or mining knowledge from a large amount of data and it also support exploring of data. This research determine whether a person is affected or not affected by heart disease which is based on their historical and real time data .In this paper Advance clustering algorithms (K means clustering algorithm) and A-priori algorithm is used for the analysis of heart disease and various type of other disease .This system is implemented on MATLAB software. MATLAB is introduced as better performance software.
Keywords: Machine learning, data mining, clustering algorithms, A-priori algorithms, Heart disease, data set, MATLAB.
Cite this Article: Manju Rani, Pooja Rani, Himanshi Sharma. A Review on Heart Disease Monitoring System by Using Machine Learning. Recent Trends in Programming Languages. 2020; 7(1): 1–6p.
Downloads
Published
Issue
Section
License
Declaration and Copyright Transfer Form
(to be completed by authors)
I/ We, the undersigned author(s) of the submitted manuscript, hereby declare, that the above manuscript which is submitted for publication in the STM Journals(s), is not published already in part or whole (except in the form of abstract) in any journal or magazine for private or public circulation, and, is not under consideration of publication elsewhere.
- I/We will not withdraw the manuscript after 1 week of submission as I have read the Author Guidelines and will adhere to the guidelines.
- I/We Author(s ) have niether given nor will give this manuscript elsewhere for publishing after submitting in STM Journal(s).
- I/ We have read the original version of the manuscript and am/ are responsible for the thought contents embodied in it. The work dealt in the manuscript is my/ our own, and my/ our individual contribution to this work is significant enough to qualify for authorship.
- I/We also agree to the authorship of the article in the following order:
Author’s name
1. ________________
2. ________________
3. ________________
4. ________________
| We Author(s) tick this box and would request you to consider it as our signature as we agree to the terms of this Copyright Notice, which will apply to this submission if and when it is published by this journal. |