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Abstract:   (48 Views)

Introduction: Increase of Colon Cancer in recent years, necessitates adopting reliable and modern methods for detecting and controlling this disease. Data mining is one such method where one of its popular applications is to detect hidden patterns among patients' data in a big database. In this study, unknown patterns of a real data set of colon cancer are investigated.

Method: In this study, data set related to 400 colorectal patients including 23 features are gathered. This information pertains to patients who referred to Oncology Ward of Shahid Faghihi Hospital in Shiraz during 1387 to 1395. In this study, when steps of Fp-Growth algorithm are fulfilled, hidden relations among these data are explored and then valuable data are given to a Colon Cancer expert to be analyzed.

Results: results show that the pathologic state and patient age have a significant effect on patients' survival rate. In addition, both males and female are more prone to rectal cancer than colon cancer, and sex does not affect survival rate. It can also be concluded that there is no significant relation between pathologic stage and demographic information. 

Type of Study: case report | Subject: Internal Medicine

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