Heart Disease Prediction System


Authors : Sadhana B S, Ashok Kumar L , Sharmila M, Raehan Khan, Dr T H Sreenivas.

Volume/Issue : Volume 4 - 2019, Issue 2 - February

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://goo.gl/gW9LvL

Thomson Reuters ResearcherID : https://goo.gl/KTXLC3

One of the potentially fatal grievous disease is heart disease that can lead to either death or a serious lifelong impairment. It is estimated by a recent survey that approximately 17.5million people die every year due to heart disease. It is predicted that the death rate may increase upto 75 million in the year 2030. Medical diagnosis is one of the most important and difficult task to be done as it plays an important role in diagnosing disease accurately and efficiently. In order to obtain accurate results an automated computer oriented decision support system must be achieved. For this purpose machine learning algorithm can be used. Presently in the field of medical science the chance of predicting heart attack is around 67%, so doctors are in need of definite decision support system.

Keywords : Computer Oriented Decision Support System, Decision Support System, Ehrs, Supervised Learning Method, Statistical Method.

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