Abstract:
Now-a-days, we can see the number of heart disease cases increasing highly. Especially old people
affected by this . It is so concerning for the world. We thought about this kind of disease and how
we could predict this in advance. Though it’s difficult to diagnose, it should be done correctly and
quickly too. We made a prediction system named heart diseases prediction system , which uses a
patient’s medical data to predict whether or not they will be diagnosed with heart disease.
The fundamental recognition of the studies paper is on which sufferers are extra likely
to expand coronary heart sickness primarily based totally on numerous clinical characteristics.
We used four machine learning algorithms to predict and classify heart disease patients such as
Decision Tree, Logistic Regression, Random Forest Classifier and k-N Neighbor . To adjust how
the version may be used to enhance the accuracy of prediction of Heart Attack in any individual ,a
very helpful approach was used . The proposed model's power changed
into pretty satisfying, because it changed into capable of are expecting proof of getting a coronary
heart sickness in a particular person the use of Logistic Regression , Random forest and Decision
Tree which showed a high level of accuracy when compared to k-N Neighbor.
