معرفی الگوریتم های مدل رده بندی درختی و کاربرد آن در تعیین عوامل مؤثر بر ابتلا به سرطان مری در استان گلستان

Background & objective: One of the common purposes of medical research is Determination of effective factors on the occurrence of event. Due to the interaction of risk factors regression models, discriminant analysis and classification procedures used. Uses of these models require making the assumption which in the medical data isn’t usually established. Therefore, alternative methods must be used. According to diversification of risk factors for of esophageal cancer, the purpose of this article is the Introduction and application of classification and regression tree for determination of risk factor for esophageal cancer in Golestan province.Methods: Data of this article gathered from case-control study. Case group contain all confirmed cases of esophageal cancer that consist of 90 male and 60 female subjects in Golestan province during one year. Two control groups were considered for each case. Control groups were selected from family of patients and neighbors and matched for age, sex, ethnic and place of residence. Data was analyzed with classification and regression tree model and by using of R software. Gini criterion was used for selection of best splitting in each node and ROC surveyed accuracy of CRT model.Results: (ethnic factors) can be effective in esophageal cancer occurrences.Results of Classification tree model showed that exposure to CT and X-ray dye (socio-environmental factors), unwashed hands after defecation, history of smoking (lifestyle factors) and family history of cancerConclusion: models results` interpretation are two essential beneficiary of these models which can use in medical sciences.Tree models don’t require the establishment of no default for making model and feasibility of tree