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Heart Disease Prediction Using Machine Learning

Taher M. GhazalUniversiti Kebangsaan Malaysia (UKM),Center for Cyber Security, Faculty of Information Science and Technology,Bangi,Malaysia,43600Amer IbrahimAmerican University in the Emirates,College of Computer and Information Technology,Dubai,United Arab EmiratesAli Sheraz AkramNCBA&E,School of Computer Science,Lahore,PakistanZahid Hussain QaisarNFC Institute of Engineering and Technology,Department of Computer Science,Multan,PakistanSundus MunirLahore Garrison University Lahore,Department of Computer Science,Lahore,PakistanShanza IslamLahore Garrion University Lahore,Department of Computer Science,Lahore,Pakistan
2023en
ABI

Annotatsiya

The heart disease cases are rising day by day and it is very Important to predict such diseases before it causes more harm to human lives. The diagnosis of heart disease is such a complex task i.e., it should be performed very carefully. The work done in this research paper mainly focuses on which patients has more chance to suffer from this based on their various medical feature such as chest pain etc. We proposed a system of heart disease prediction that is used to diagnose whether the patient is a victim or not by using the previous medical features of the patient. Support vector machine and k-nearest neighbor algorithms of machine learning are used to predict and classify the patient with heart disease. The models gave satisfactory results and were capable for predicting a heart disease by using k-nearest neighbor and support vector machine which gave a good accuracy in contrast to the algorithms that were used in the previous research such as naive bayes etc.

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