Introduction: The aim of this study was to determine the performance of data mining techniques for predicting the causes of traumatic brain injuries in Khatamolanbya hospital, Zahdan city.
Method: In this cross–sectional, the study population included all patients who died of brain injury. Data were collected by the use of a researcher- made check list, provided under the direct observation of authorities in this area and analyzed by the data mining software of Clementine 12.0.
Results: According to the results of this algorithm, C5.0 decision tree algorithm has an accuracy of 81.4 percent, the highest precision; then, the algorithm is C & R(The Classification and Regression) with 77.8 percent.
Conclusion: Overall, it can be concluded from the decision tree algorithm that age is one of the leading causes of traumatic brain injuries . The results showed that all the cases involving traumatic lesions of the brain lead to the patient’s death.. Although in some algorithms, some
کلید واژگان :
Data mining, Prediction of the factors of traumatic brain injuries
