Inspiration
With the increasing number of heart attacks in recent years mainly after Covid, it seems to be necessary to find a solution that indicates us whether we are prone to any heart diseases.
What it does
Detects possible heart diseases using Machine Learning
How we built it
With the use of the dataset provided by kaggle.com which gave us information about the heart condition in 70,000 patients. We use various algorithms like Random Forest Classification, Decision Tree, KneighbourClassfier, SGDClassifier, Linear Regression, Logistic Regression, and XGBClassifier to find the most accurate results.
Challenges we ran into
Determining the most accurate algorithm and testing it over and over again to find the accuracy of the system. Linking this system to a web application so that anyone can know their heart condition on the go.
Accomplishments that we're proud of
We as beginners are proud to develop an application that we can develop further on and improve the working and thus potentially help the lives of thousands of people.
What we learned
How to use basic Machine Learning applications using Python, Running and saving the test cases for further use, and Creating a web application that links with the machine learning algorithm to the best possible solution.
What's next for Heart Disease Detection System
Increasing the number of test cases and making it readily available for the general people and thus, increasing the accuracy of the system to provide an efficient and safe output.
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