How to estimate and predict the expenses incurred by diabetes treatment using Artificial Neural Network (ANN)
Authors: Mohammad Mahboubi1, Mehrali Rahimi2, Mahshid Mohebbi3, Fariba Ghahramani4*
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Diabetes is considered a great health problem due to its economic importance and the fact that it is a chronic disease. The aim of this study was to determine the costs imposed on diabetic patients using Artificial Neural Network. The study data were gathered by random-ly investigating 396 individuals who referred to Kermanshah diabetic center. In this study, Artificial Neural Network using Multiple Layer Perception (MLP) was used to investigate the costs imposed on diabetic patients. In this research, the variable related to treatment of diabetes was calculated through neural network in 8 different output layers. The eight output layers of expenses included physician's vis-it, medication, tests, hospitalization, radiology, treatment of symptoms, transportation, and counseling. In this study, the highest annual expenses were related to medication, tests, and radiology. In addition, the patients who presented the symptoms spent more money for treatment. Considering need to efficiently use medical facilities, it is necessary use ways which be applied to predict the medical ex-penses. We came to conclusion that neural network had great advantages over the regression model and could be used as an efficient tool for prediction of expenses and can replace the classical and statistical models.