Volume 3, Issue 2 (3-2018)                   2018, 3(2): 20-28 | Back to browse issues page

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khedri M, ghazi saeedi M, Sheikh taheri A, zareei J. Relationship between socioeconomic status and burn patients survive using data mining. Journal of Modern Medical Information Sciences. 2018; 3 (2) :20-28
URL: http://jmis.hums.ac.ir/article-1-104-en.html
master of science ahvaz university of medical science
Abstract:   (819 Views)
Introduction: In all societies, burn is a health challenge and more than any other truma causes physiologic  mental economic and health disorder both for the patient and its family.The highest rates of burns are found in underdeveloped and developing regions. Cases such as lifestyle, social, economic, and cultural levels of society can change the type and type of burns. Given that data mining is growing and new, it is also of great importance to medical data. Therefore, in this project, the intention is to collect data using actual data mining techniques and in view of the prevalence of burns in developing countries, a model for establishing a meaningful relationship between the economic and social status of individuals Who develop burns as a result of their treatment.
Methods: The present study is analytic-descriptive and is based on retrospective nature. The population of the study consists of 553 patients all adult burn patients who were hospitalized in Ayatollah Taleghani hospital in Ahvaz for 3 years ( 1388-1390). After pre-processing of data, the insight belonging to 546 were closely examined. The collected data were computed by using spss22, IBM Modeler 14.2. and algorithm of C5,CHAID and CART.
Results: The predicted model for outcome of burn for patients conducted through selected algorithms in order of priority include factors of burn ,occupation, capsule at home, place of incident, residential area , rate of income, intent, gender and education.
Comparison of the accuracy of the algorithms, the highest accuracy of the C & R algorithm (0.87), The most characteristic of the CHAID algorithm (0.98) And the most sensitivity was obtained for the C & R algorithm (0.50). Given the superiority of the C & R model, this model was recognized as the top model in terms of the accuracy and sensitivity of the models.
Conclusion: Due to the average accuracy of suggested models, these models are both valid and attributable. The results of this study can be useful for predicting the impact of socioeconomic factors on burnout outcomes.
 
     
Type of Study: Applicable | Subject: Special
Received: 2017/01/30 | Accepted: 2018/03/25 | Published: 2018/03/25

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