Volume 10, Number 3 (Vol 10, No.3 2014)                   irje 2014, 10(3): 1-8 | Back to browse issues page

XML Persian Abstract Print

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

Asadabadi A, Bahrampour A, Haghdoost A. Prediction of Breast Cancer Survival by Logistic Regression and Artificial Neural Network Models. irje. 2014; 10 (3) :1-8
URL: http://irje.tums.ac.ir/article-1-5273-en.html

1- , abahrampour@yahoo.com
Abstract:   (6733 Views)

  Background and Objectives : recent years, considerable attention has been paid to statistical models for classification of medical data according to various diseases and their outcomes. Artificial neural networks have been successfully used for pattern recognition and prediction since they are not based on prior assumptions in clinical studies. This study compared two statistical models, artificial neural network and logistic regression, to predict the survival of patients with breast cancer.

  Methods: Two models were applied on cancer registry data, Kerman, southeast of Iran, to predict survival. The data of 712 breast cancer patients in the age group 15 to 85 years was used in this study. The logistic regression and three-layer perceptron neural network models were compared in terms of predicting the survival. Sensitivity, specificity, prediction accuracy, and the area under ROC curve were used for comparing the two models.

  Results : In this study, the sensitivity and specificity of logistic regression and artificial neural network models were (0.594, 0.70) and (0.621, 0.723), respectively. Prediction accuracy and the area under ROC curve for two models were (0.688, 0.725) and (0.70, 0.725), respectively.

  Conclusion: Although there were insignificant differences in the performance of the two models for predicting the survival of the patients with breast cancer, the corresponding results of artificial neural network were more appropriate for predicting survival in such data.

Full-Text [PDF 459 kb]   (2757 Downloads)    
Type of Study: Research | Subject: General
Received: 2015/02/21 | Accepted: 2015/02/21 | Published: 2015/02/21

Add your comments about this article : Your username or email:
Write the security code in the box

Send email to the article author

© 2017 All Rights Reserved | Iranian Journal of Epidemiology

Designed & Developed by : Yektaweb