Journal of Health and Biomedical Informatics

Introduction: Gastric cancer is the second cause of death from cancer after lung cancer in the world It`s incidence is varied in different regions of the words. Due to the prevalence rate of the disease and high mortality rates for gastric cancer in the country, it is necessary to examine the influential factors in the incidence of this disease by more accurately and scientific methods. The purpose of this study is to examine this factor with data mining techniques.
Method: The required data for this study was collected from patients referring to Imam Reza Hospital, Tabriz. After applying data pre-processing, totally 490 records were collected in an Excel file samples including 220 cancer cases and 270 normal specimens. The best rules based on the datasets were extracted by using Apriori algorithm implemented in MATLAB software and final data set.
Results: In this study, gastric cancer datasets and features affecting the incidence of this disease have been used for the first time. The results showed that risk for gastric cancer in people with cardiovascular disease are less‌. In addition, gastric reflux is associated with not using salt and milk, and high salt intake. Gastric reflux has also the most influence on creating this disease. Some rules were obtained by using Apriori algorithm that can be used as a model to predict the status of patients and the incidence of this disease.
Conclusion: Nowadays Due to massive amounts of medical data, knowledge can be extracted from datasets by using data mining approach. In this study, some rules were extracted by using Apriori algorithm that can provide physicians with great help to examine the causes of this disease.