EN
TR
DETERMINATION OF HEART ATTACK RISK ON PATIENTS DATA by DATA MINING APPLICATIONS
Öz
In this study, it has been investigated that feasibility of data mining which is used to extract meaningful knowledge in order to effect to decision making processes in health field. As an example to a case study, it has been tried to obtain that determining the factors which trigger heart attacks by defining common changes in blood values of patients whom have got heart attacks previously. Success of the analysis done has been measured by testing the obtained results on a group of patients. In the study, Apriori and GRI algorithms stemming from association rule algorithms have been used; success of rule sets created by these algorithms has been investigated by making several comparisons. As the result, several patterns meant to pre-signals determining heart attacks from data of the patient group which have the blood values have been put forth.
Anahtar Kelimeler
Kaynakça
- Şentürk, Z.K., The Diagnosis of Cancer with Data Mining, Master Thesis, Düzce University, Düzce, p.58, 2011.
- Çakır, F., Akgöbek, Ö, Designing An Expert System in Data Mining, Academic Information 2009 Conference, Harran University, Şanlıurfa, Proceedings Book, p.801–806, 2009.
- Savaş, S. Topaloğlu, N. ve Yılmaz, M., Data Mining and Practices in Turkey, İstanbul Commerce University, Journal of Natural and Applied Sciences, Year:11, No: 21, p. 1-23, 2012
- Han, J. ve Kamber, M., Data Mining Concepts and Techniques, Morgan Kauffmann Publishers Inc., 1-35., 2006.
- Azimli, M., Data Mining Applications in Medicine, Master Thesis, Gazi University, Ankara,. p.63, 2011.
- Obenshain, K., Application of data mining techniques to healthcare data, Data Infect Control Hosp Epidemiol, 25: 690-695, 2004.
- Koyuncugil, A.S. ve Özgülbaş, N. (2009) Data Mining: Use and Applications in Medicine and Health Services, Journal of Information Technologies, Vol.2, No:2, p.21-32, 2009.
- Güleç, S., Global Risk of Cardiovascular Disease and Objectives, Turkish Society of Cardiology, Volume:37, No:2, p.1–10, 2009.
Ayrıntılar
Birincil Dil
İngilizce
Konular
Mühendislik
Bölüm
Araştırma Makalesi
Yayımlanma Tarihi
7 Nisan 2015
Gönderilme Tarihi
26 Mart 2015
Kabul Tarihi
2 Nisan 2015
Yayımlandığı Sayı
Yıl 2015 Cilt: 1 Sayı: 1
APA
Tarımer, İ., & Elmas, F. (2015). DETERMINATION OF HEART ATTACK RISK ON PATIENTS DATA by DATA MINING APPLICATIONS. Mugla Journal of Science and Technology, 1(1), 18-23. https://doi.org/10.22531/muglajsci.209994
AMA
1.Tarımer İ, Elmas F. DETERMINATION OF HEART ATTACK RISK ON PATIENTS DATA by DATA MINING APPLICATIONS. MJST. 2015;1(1):18-23. doi:10.22531/muglajsci.209994
Chicago
Tarımer, İlhan, ve Fatih Elmas. 2015. “DETERMINATION OF HEART ATTACK RISK ON PATIENTS DATA by DATA MINING APPLICATIONS”. Mugla Journal of Science and Technology 1 (1): 18-23. https://doi.org/10.22531/muglajsci.209994.
EndNote
Tarımer İ, Elmas F (01 Nisan 2015) DETERMINATION OF HEART ATTACK RISK ON PATIENTS DATA by DATA MINING APPLICATIONS. Mugla Journal of Science and Technology 1 1 18–23.
IEEE
[1]İ. Tarımer ve F. Elmas, “DETERMINATION OF HEART ATTACK RISK ON PATIENTS DATA by DATA MINING APPLICATIONS”, MJST, c. 1, sy 1, ss. 18–23, Nis. 2015, doi: 10.22531/muglajsci.209994.
ISNAD
Tarımer, İlhan - Elmas, Fatih. “DETERMINATION OF HEART ATTACK RISK ON PATIENTS DATA by DATA MINING APPLICATIONS”. Mugla Journal of Science and Technology 1/1 (01 Nisan 2015): 18-23. https://doi.org/10.22531/muglajsci.209994.
JAMA
1.Tarımer İ, Elmas F. DETERMINATION OF HEART ATTACK RISK ON PATIENTS DATA by DATA MINING APPLICATIONS. MJST. 2015;1:18–23.
MLA
Tarımer, İlhan, ve Fatih Elmas. “DETERMINATION OF HEART ATTACK RISK ON PATIENTS DATA by DATA MINING APPLICATIONS”. Mugla Journal of Science and Technology, c. 1, sy 1, Nisan 2015, ss. 18-23, doi:10.22531/muglajsci.209994.
Vancouver
1.İlhan Tarımer, Fatih Elmas. DETERMINATION OF HEART ATTACK RISK ON PATIENTS DATA by DATA MINING APPLICATIONS. MJST. 01 Nisan 2015;1(1):18-23. doi:10.22531/muglajsci.209994
Cited By
Analysis of the Association Between Vitamin D Deficiency and Other Diagnoses of Patients by Data Mining Techniques
Sakarya University Journal of Computer and Information Sciences
https://doi.org/10.35377/saucis.03.01.677676