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Predictor

Inspiration

In the recent year in India there has been a 50% increase in the heart disease and strokes among people.At ages 30-69 years, of 1.3 million cardiovascular deaths, 0.9 million (68.4%) were caused by coronary heart disease

What it does

It is a webapp which uses machine learning to predict the chances of the person having a heart disease .

How we built it

First We Implemented the ML model(logistic regression model) on the data set then we found that the data set followed a generalized relation(refrence IEEE paper) which we used for heart predictor on our website.

Challenges we ran into

Finding the pattern in the dataset or the generalized relation, Displaying the percentage using d3.js.

Accomplishments that we're proud of

Achieving the accuracy of 85% in the model.

What we learned

Tackling the real life problems .

What's next for Heart Disease Analysis and Prediction

Future Implementation using tracking sensor devices like fitbit , iWatches etc to collect the data directly and predicting the heart disease vulnerability .