Title of article :
Predictive Factors of Advanced Colonic Adenomas and Cancer Using Data Mining
Author/Authors :
Fatemian, Atieh Sadat Faculty of Economics and Social Sciences - Alzahra University , Abdolvand, Neda Faculty of Economics and Social Sciences - Alzahra University , Salimzadeh, Hamideh Digestive Disease Research Institute - Shariati Hospital , Delavari, Alireza Digestive Disease Research Institute - Shariati Hospital
Pages :
7
From page :
192
To page :
198
Abstract :
BACKGROUND Colorectal cancer is the third common cancer in Iran. In this study we aimed to identify factors associated with the prevalence of advanced colonic neoplasms among a high-risk population. METHODS Participants were 474 first degree relatives of patients with colon cancer who underwent a screening colonoscopy at Digestive Disease Research Institute, Shariati Hospital affiliated to Tehran University of Medical Sciences. Features examined in this study were age, sex, body mass index, Aspirin use, smoking, and relationship type with patients with cancer in family. Also, patient’s age at the time of cancer diagnosis, number and sex of the patients with colon cancer in the family were assessed. Data analysis was performed by data mining methods using K-Medoid clustering and decision tree C4.5. RESULTS Results showed that female sex of the patients with colon cancer and their young age (< 60 years old) at the time of cancer diagnosis were important predictive factors for the prevalence of colorectal advanced neoplasms among their family members. CONCLUSION Data mining methods were found to be applicable in recognizing predictive factors of colorectal advanced neoplasms in each cluster and tree.
Keywords :
Colorectal Cancer , Data Mining , Clustering , Decision Tree , Crisp Methodology
Journal title :
Middle East Journal of Digestive Diseases(MEJDD)
Serial Year :
2019
Record number :
2500877
Link To Document :
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