Mining of rectal cancer data based on decision tree algorithm and logistic regression algorithm

Abstract:
Colorectal cancer can occur at any age, but most patients are over the age of 40. Colorectal cancer is also one of the most preventable tumors. It usually arises from "polyps" that are noncancerous new growths of the colon or rectal epithelium. If it is screened, detected early and removed, it can prevent it from becoming a tumor. The medical community believes that bowel cancer is the most curable cancer if detected early. The purpose of this study was to use decision tree and Logistic regression algorithm to establish early colorectal cancer based on various non-invasive factors such as basic information, dietary habits, recent main symptoms, family history of disease, past history of disease, and serological examination in patients with colorectal cancer. A cancer risk prediction model, while analyzing the factors that have an important impact on early colorectal cancer risk prediction, in order to assist clinical screening of early colorectal cancer risk before invasive colorectal cancer endoscopy and pathological biopsy, which can further promote the improvement of early colorectal cancer risk Colorectal cancer detection rate.