Users Online: 1991
» Articles published in the past year
To view other articles click corresponding year from the navigation links on the side navigation bar.
Letters to Editor
Letters to the Editor
Short Original Article
Export selected to
Show all abstracts
Show selected abstracts
Export selected to
Add to my list
Application of data mining techniques in predicting coronary heart disease: A systematic review
Saeed Saeedbakhsh, Mohammad Sattari, Maryam Mohammadi, Jamshid Najafian
Int J Env Health Eng
2021, 10:5 (30 September 2021)
The early detection of cardiovascular diseases by noninvasive and low-cost methods such as data mining techniques has been considered by many researchers. This study intends to review the studies performed on the prognosis of coronary heart disease using data mining techniques.
Materials and Methods:
The published studies in English between 2001 and 2021 that the use classification methods to predict coronary heart disease were considered. Databases such as ScienceDirect, Web of Science, and ScoPURs were considered as searchable databases. After searching, 348 articles were retrieved. After removing duplicates and evaluating the articles, finally, 20 articles were used.
The three data mining techniques support vector machine (SVM), neural network, and naive Bayes which were the most used among the studies. In the most studies, risk factors age, blood pressure, gender, diabetes, and chest pain were used. The accuracy was the most-used measure. The Alizadeh Sani dataset was the most used among the studies.
Techniques such as SVM and neural network have performed better than other techniques. The output of these techniques can be used as a decision support system so that clinicians can enter various risk factors such as age, blood pressure, gender, diabetes, and chest pain and then view system output.
[HTML Full text]
[Mobile Full text]
[Sword Plugin for Repository]
Month wise articles
Figures next to the month indicate the number of articles in that month
Copyright and Disclaimer
© International Journal of Environmental Health Engineering | Published by Wolters Kluwer -
Online since 21 March, 2012