ACCURATE PREDICTION OF CORONARY ARTERY DISEASE USING BIOINFORMATICS ALGORITHMS

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

SHAFIEE HAJAR; EBRAHIMI MANSOUR

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: QOM UNIVERSITY OF MEDICAL SCIENCES JOURNAL Year:2016 | Volume:10 | Issue:4 Page(s): 22-35

Download Full-Text

Persian Verion

View:

2,266

Download:

Cites:

Information Journal Paper

Title

ACCURATE PREDICTION OF CORONARY ARTERY DISEASE USING BIOINFORMATICS ALGORITHMS

Author(s)

SHAFIEE HAJAR | EBRAHIMI MANSOUR | Issue Writer Certificate

Keywords

HEART DISEASESQ2

CORONARY ARTERY DISEASESQ2

COMPUTATIONAL BIOLOGYQ1

SUPPORT VECTOR MACHINEQ1

Abstract

Background and Objectives: Cardiovascular disease is one of the main causes of death in developed and Third World countries. According to the statement of the World Health Organization, it is predicted that death due to heart disease will rise to 23 million by 2030. According to the latest statistics reported by Iran’s Minister of health, 3.39% of all deaths are attributed to cardiovascular diseases and 19.5% are related to myocardial infarction. The aim of this study was to predict coronary artery disease using data mining algorithms.Methods: In this study, various bioinformatics algorithms, such as decision trees, neural networks, SUPPORT VECTOR MACHINEs, clustering, etc., were used to predict coronary heart disease. The data used in this study was taken from several valid databases (including 14 data).Results: In this research, data mining techniques can be effectively used to diagnose different diseases, including coronary artery disease. Also, for the first time, a prediction system based on SUPPORT VECTOR MACHINE with the best possible accuracy was introduced.Conclusion: The results showed that among the features, thallium scan variable is the most important feature in the diagnosis of heart disease. Designation of machine prediction models, such as SUPPORT VECTOR MACHINE learning algorithm can differentiate between sick and healthy individuals with 100% accuracy.

Cites

References

No record.

Cite

APA: Copy

SHAFIEE, HAJAR, & EBRAHIMI, MANSOUR. (2016). ACCURATE PREDICTION OF CORONARY ARTERY DISEASE USING BIOINFORMATICS ALGORITHMS. QOM UNIVERSITY OF MEDICAL SCIENCES JOURNAL, 10(4), 22-35. SID. https://sid.ir/paper/131848/en

Vancouver: Copy

SHAFIEE HAJAR, EBRAHIMI MANSOUR. ACCURATE PREDICTION OF CORONARY ARTERY DISEASE USING BIOINFORMATICS ALGORITHMS. QOM UNIVERSITY OF MEDICAL SCIENCES JOURNAL[Internet]. 2016;10(4):22-35. Available from: https://sid.ir/paper/131848/en

IEEE: Copy

HAJAR SHAFIEE, and MANSOUR EBRAHIMI, “ACCURATE PREDICTION OF CORONARY ARTERY DISEASE USING BIOINFORMATICS ALGORITHMS,” QOM UNIVERSITY OF MEDICAL SCIENCES JOURNAL, vol. 10, no. 4, pp. 22–35, 2016, [Online]. Available: https://sid.ir/paper/131848/en

Related Journal Papers