Data mining of the performance of medical centers and harm reduction in Isfahan province in correcting and preventing drug addiction

In addition to physical and psychological harm, drug addiction also led to social and economic complications and problems, such as the increase in drug-related crimes such as crime and theft, poverty and begging, and the waste of large material assets of countries. The purpose of this study is to identify and compare the model of factors related to drug addiction in treatment and harm reduction centers and the Association of Anonymous Addicts in Isfahan province to correct and prevent drug addiction. The research method is quantitative and descriptive-analytical. The statistical population includes all people referring to treatment and harm reduction centers and anonymous addicts associations in the second half of 1399. 1593 questionnaires were provided to the centers as a sample and 1459 questionnaires were analyzed by removing the distortions. Drug addiction was assessed with Wade and Butcher Addiction Readiness Scale α = 0.9. The results showed that the random decision tree algorithm has the highest accuracy of prediction, in each data set the appropriate data algorithm should be explored. The algorithms used in this study have a good ability to predict the tendency to use drugs that using the effective factors found, the necessary measures can be taken to prevent third parties. Also, using the rules, it was found that the tendency of new people referring to the centers can be predicted.