Ali Abdolahi - Sama Technical and Vocational Training College, Islamic Azad University, Bandar Mahshahr Branch, Bandar Mahshahr, Iran
Vali Nowzari - Department of Physical Education, Islamic Azad University, Arsanjan Branch, Arsanjan, Iran
Ali Pirzad - Department of Government Management, Islamic Azad University, Yasooj Branch, Yasooj, Iran
Seyed Ehsan Amirhosseini - Department of Sport Management, Islamic Azad University, Yasooj Branch, Yasooj, Iran

Introduction: Health companies need investment for development. Due to the high risk of their activities, it is very difficult to attract investment for this field, but this lack of financial resources leads to the failure of these companies, so providing a model for predicting profits and losses in companies is very important and functional.Material and Methods: In this study, a combination of two logistic regression algorithms and differential analysis were used to design a profit and loss forecasting model. Also, the information of ۲۰ companies in the field of health was used to evaluate the proposed model. ۱۰ profitable companies and ۱۰ loss-making companies were selected and for each company, nine variables independent of the financial information of these companies were collected.Results: The designed prediction model was implemented on the data in this study. To do this, the data were divided into two sets: training and testing. The prediction model was implemented on training data and evaluated by test data and reached ۹۹.۶۵% sensitivity, ۹۴.۷۵% specificity and ۹۶.۲۸% accuracy. The proposed model was then compared with the methods of decision tree C۴.۵, Bayesian, support vector machine, nearest neighborhood and multilayer neural network and it was found to have a better output.Conclusion: In this study, it was found that the risk in the field of health investment can be reduced, so the profit and loss situation of health companies can be predicted with appropriate accuracy. It was also found that the combination of logistic regression and differential analysis algorithms can increase the accuracy of the prediction model.

Data Mining Forecast, Financial, Differential Analysis, Logistic Models