dc.contributor.author |
Desai, Geeta |
|
dc.contributor.author |
Mirkar, Naif Shaukat Rahat (17DET50) |
|
dc.contributor.author |
Naif, Shaukat Rahat (17DET50) |
|
dc.contributor.author |
Mohammed, Aqib Mohammed Sohel Asiya (17DET52) |
|
dc.date.accessioned |
2021-11-09T07:09:06Z |
|
dc.date.available |
2021-11-09T07:09:06Z |
|
dc.date.issued |
2020-05 |
|
dc.identifier.uri |
http://localhost:8080/xmlui/handle/123456789/3632 |
|
dc.description.abstract |
Cardiovascular 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.iso |
en |
en_US |
dc.publisher |
AIKTC |
en_US |
dc.subject |
Project Report - EXTC |
en_US |
dc.title |
Heart Disease Prediction System using machine learning |
en_US |
dc.type |
Other |
en_US |