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ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
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Paper Title: Prediction Of Heart Disease Using Machine Learning
Authors Name: Akash Chandra Patel , Manish Mishra , Anash Shameem , Sunil Chaurasiya , Prof. Abhishek Saxena
Unique Id: IJSDR1904075
Published In: Volume 4 Issue 4, April-2019
Abstract: In today's environment Heart disease is a major life-threatening disease that can cause either death or a serious long term disability [1] since its diagnosis in most cases depends upon a complex combination of clinical and pathological data. Since medical diagnosis is a complicated task and plays a vital role in saving human lives so it needs to be executed accurately and efficiently but there is lack of effective tools to discover hidden relationships and trends in e-health data. Due to this complexity, an appropriate and accurate computer-based automated decision support system is required to reduce the cost for achieving clinical tests. In this paper, we proposed a Heart Disease prediction system that can assist medical professionals in predicting the status of heart disease based on the clinical data of patients. The main objective of this study is to build a model that can predict the occurrence of heart disease, based on a combination of features (risk-factors). Different machine learning classification techniques will be implemented and compared upon standard performance metric such as accuracy for comparison between different machine learning algorithms.
Keywords: Machine Learning, Heart Disease Prediction
Cite Article: "Prediction Of Heart Disease Using Machine Learning", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.4, Issue 4, page no.354 - 357, April-2019, Available :http://www.ijsdr.org/papers/IJSDR1904075.pdf
Downloads: 000102098
Publication Details: Published Paper ID: IJSDR1904075
Registration ID:190425
Published In: Volume 4 Issue 4, April-2019
DOI (Digital Object Identifier):
Page No: 354 - 357
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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