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dc.contributor.authorDesai, Geeta-
dc.contributor.authorMirkar, Naif Shaukat Rahat (17DET50)-
dc.contributor.authorNaif, Shaukat Rahat (17DET50)-
dc.contributor.authorMohammed, Aqib Mohammed Sohel Asiya (17DET52)-
dc.date.accessioned2021-11-09T07:09:06Z-
dc.date.available2021-11-09T07:09:06Z-
dc.date.issued2020-05-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/3632-
dc.description.abstractCardiovascular disease one of the lethal disease in the world.Around 17 million people lost their life because of Cardiovascular disease.Particularly myocardial infraction, also known as heart attack.Which lead to a necessity to stored the symptoms and bad health habits which has the end result of cardio vascular disease.In order to diagnosed the cardio vascular one has to go through various tests like auscultation, ECG,blood pressure,cholesterol and blood sugar.As the condition of the patient becomes more and more critical the significantly increase in tests with respect to time therefore prioritization of the tests became very important.Health habits lead to the cardiovascular disease need to be recognised and certified precaution must be taken.As data increasing day by day machine learning is an provocative and widely increasing field which lead to the output in a short time for the large amount of data.The objective of this project is to predict the heart disease using machine learning algorithm. From 100 percent of the data 70 percent will be used to trained and 30 percent will be tested.Classifiers like K-Nearest Neighbour and Support Vector Machine(SVM) are used to train data. Keywords: Python, Machine learning, Support vector machine (SVM), KNearest Neighbors,Graphic User Interface(GUI).en_US
dc.language.isoenen_US
dc.publisherAIKTCen_US
dc.subjectProject Report - EXTCen_US
dc.titleHeart Disease Prediction System using machine learningen_US
dc.typeOtheren_US
Appears in Collections:EXTC Engineering - Project Reports

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