Tehran University of Medical Sciences Iranian Journal of Public Health 2251-6085 46 11 2017 11 01 1563 1571 Houriyeh EHTEMAM Health Services Management Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran Mitra MONTAZERI Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran AND Computer Engineering Department, Faculty of Engineering, Shahid Bahonar University, Kerman, Iran Reza KHAJOUEI Medical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran Raziyeh HOSSEINI Health Information Sciences Dept., Faculty of Management and Medical Information Sciences, Kerman University of Medical Sciences, Kerman, Iran Ali NEMATI Hematology and Oncology, Faculty of Medicine, Kerman University of Medical Sciences, Kerman, Iran Vahid MAAZED Hematology and Oncology, Faculty of Medicine, Kerman University of Medical Sciences, Kerman, Iran 2017 11 01 2017 11 01 Background: Breast cancer is one of the most common cancers with a high mortality rate among women. Prognosis and early diagnosis of breast cancer among women society reduce considerable rate of their mortality. Nowadays, due to this illness, try to be setting up intelligent systems, which can predict and early diagnose this cancer, and reduce mortality of women society. Methods: Overall, 208 samples were collected from 2014 to 2015 from two oncologist offices and Javadalaemeh Clinic in Kerman, southeastern Iran. Data source was medical records of patients, then 64 data mining models in MATLAB and WEKA software were used, eventually these measured precision and accuracy of data mining models. Results: Among 64 data mining models, Bayes-Net model had 95.67% of accuracy and 95.70% of precision; therefore, was introduced as the best model for prognosis and diagnosis of breast cancer. Conclusion: Intelligent and reliable data mining models are proposed. Hence, these models are recommended as a useful tool for breast cancer prediction as well as medical decision-making.     https://ijph.tums.ac.ir/index.php/ijph/article/view/11489 https://ijph.tums.ac.ir/index.php/ijph/article/download/11489/5827