Heart Disease Prediction Using Machine Learning Techniques

被引：0

作者：

Sipail, Herold Sylvestro ^{[1
]}

Ahmad, Norulhusna ^{[1
]}

Noor, Norliza Mohd ^{[1
]}

机构：

[1] Univ Technol Malaysia, Razak Fac Technol & Informat, Kuala Lumpur Campus, Kuala Lumpur, Malaysia

来源：

1ST NATIONAL BIOMEDICAL ENGINEERING CONFERENCE (NBEC 2021): ADVANCED TECHNOLOGY FOR MODERN HEALTHCARE | 2021年

关键词：

Heart Disease; Weka; Machine Learning; ALGORITHMS;

D O I：

10.1109/NBEC53282.2021.9618753

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Heart disease is the leading cause of death in the developed world. Early detection of the heart disease can prevent death, as well as other disease that is related to it such as dementia. Therefore, studies in preventing the risks of having a stroke or heart attack required. Using machine learning techniques, the aim of this study is to evaluate the accuracy of supervised learning techniques in predicting heart disease based on the dataset obtained from University of California Irvine data repository. The result from this study shows that Naive Bayes and Bayesian Network has better estimated accuracy in Weka for the data set, while both Bayesian Network and J48 may give useful insight with Weka generated visualization.

引用

页码：48 / 52

页数：5

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