One of the biggest challenges in heart disease is its detection. While there are existing tools that can predict heart diseases, calculating the probability of heart diseases is either expensive or inefficient. Early detection of heart diseases is extremely important as it can reduce the death rate and complications it will lead to. However, it is not possible to accurately monitor patients every day. Moreover, since this monitoring requires experience, time, and expertise, the patient cannot be consulted by the doctor 24 hours a day. Since we have a good amount of data in today's world, we can come up with a solution to this problem by analyzing the data and using various machine learning techniques. In conclusion, medical data can be used for health diagnosis using appropriate analysis and methods. In this project, we will try to analyze health data and predict the potential heart diseases.
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A machine learning study using ensemble methods to predict heart disease risk.
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