One of the complex tasks in healthcare industry is predicting of heart disease and it requires more experience and knowledge.
Some of the ways of predicting heart diseases are ECG, stress test and heart MRI etc.
So, to solve that problem I have come up with a solution that takes 14 parameters to predict whether a person is infected by a heart disease or not.
These parameters are used to improve an accuracy level and provide best results.
Parameters include :
1. age
2. gender
3. cp(chest pain)
4. trestbps(resting blood pressure in mm Hg on admission to the hospital)
5. chol(serum cholestoral in mg/dl)
6. fbs(fasting blood sugar > 120 mg/dl)
7. restecg (resting electrocardiographic results)
8. thalach(maximum heart rate achieved)
9. exang(exercise induced angina)
10. oldpeak(ST depression induced by exercise relative to rest)
11. slope(the slope of the peak exercise ST segment)
12. ca(number of major vessels (0-3) colored by flourosopy)
13. thal
14. num(the predicted attribute(angiographic disease status))
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