Open AccessHEART DISEASE PREDICTION USING MACHINE LEARNING
Author(s) -
V Biksham,
V. Srujana,
I Meghana,
B Harshath,
G Tarun
Publication year - 2022
Publication title -
ymer
Language(s) - English
Resource type - Journals
ISSN - 0044-0477
DOI - 10.37896/ymer21.04/48
Subject(s) - machine learning , construct (python library) , computer science , random forest , artificial intelligence , interface (matter) , decision tree , heart disease , disease , tree (set theory) , medicine , mathematical analysis , mathematics , bubble , pathology , maximum bubble pressure method , parallel computing , cardiology , programming language
There is a great saying that is “Health is the most valuable Wealth”,this is because people may have great ideas, money and many things but everything can be done only when our health supports us. The main motto of our project is “Prevention is always better than the cure”.In this project we use the technology for early detection of heart diseases. These days whole world people are dying because of the hear diseases and even in many cases these are sudden deaths, So in this project we design a machine learning model which can predict the heart diseases. This machine learning model predicts whether a person can have a heart disease or not based on the information or the symptom the person enters into the system. Here we are using the machine learning algorithms like the Decision Tree, Random Forest, KNN algorithms for precise prediction of the result. Every project is incomplete without a proper interface to the entire model so for the user interface here we are using the Tkinter Interface. For the training purpose we are using a predefined dataset which we get it from the kaggle website. So in this way we construct our entire model.