اکثر مکاتبات کومش از طریق ایمیل سایت می باشد.
لطفا Spam ایمیل خود را نیز چک نمایید.
   [Home ] [Archive]   [ فارسی ]  
:: Main :: About :: Current Issue :: Archive :: Search :: Submit :: Contact ::
:: Volume 19, Issue 1 ( Winter 2017, 19 (1) 2017) ::
koomesh 2017, 19(1): 241-247 Back to browse issues page
Joint prediction of occurrence of heart block and death in patient with myocardial infarction with artificial neural network model
Negin-sadat Mirian, Morteza Sedehi , Soleiman Kheiri, Ali Ahmadi
Abstract:   (1646 Views)

Introduction: When it is desired to examine occurrence of two events simultaneously, it is common to use bivariate statistical models such as bivariate logistic regression. Due to the limitations of classical methods in real situations, other methods such as artificial neural networks (ANN) are concerned. The aim of this study was comparing the predictive accuracy of bivariate logistic regression and artificial neural network models in diagnosis of death occurrence and heart block in myocardial infarction patients.

Material and Methods: In this study, data was taken from a census in a cross-sectional study in which 263 patients with myocardial infarction cases who admitted to Hajar hospital heart care in 2013 to 2014. Gender, type of stroke, history of diabetes, previous history of hypertension, lipid disorders, history of heart disease, cardiac output fraction, systolic blood pressure, diastolic blood pressure, fasting and non-fasting blood sugar, cholesterol, triglycerides, low-density cholesterol, smoking, type of treatment, the troponin enzymes and insurant type were considered as explanatory variables and occurrence of death and heart block were used as dependent variables. Bivariate logistic regression and neural network model was fitted. Both models were predicted and the accuracy of them were compared. Models were fitted by MATLAB2013a and Zelig in R3.2.2.

Results: Predictive accuracy of bivariate logistic regression model was 77.7% for the training and 78.48% for the test data. In ANN model, LM and OSS algorithms had best performance with 83.69% and 83.15% predictive accuracy for training data and 84.81% and 83.54% for testing data, respectively.

Conclusion: This research showed that the neural network method is more accurate than bivariate logistic regression to joint predicting the occurrence of death and heart block in patients with myocardial infarction.

Keywords: Artificial Neural Network, Bivariate Logistic Regression, Myocardial Infarction
Full-Text [PDF 503 kb]   (410 Downloads)    
Type of Study: Research | Subject: General
Received: 2016/01/3 | Accepted: 2016/09/14 | Published: 2017/01/3
Send email to the article author

Add your comments about this article
Your username or Email:

CAPTCHA


XML   Persian Abstract   Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

Mirian N, Sedehi M, Kheiri S, Ahmadi A. Joint prediction of occurrence of heart block and death in patient with myocardial infarction with artificial neural network model. koomesh. 2017; 19 (1) :241-247
URL: http://koomeshjournal.semums.ac.ir/article-1-3172-en.html


Volume 19, Issue 1 ( Winter 2017, 19 (1) 2017) Back to browse issues page
کومش Koomesh
Persian site map - English site map - Created in 0.06 seconds with 32 queries by YEKTAWEB 4006