Using the Logistic Regression Model in Studding the Assistant Factors to Diagnose Bladder Cancer

Abstract

The cancer is one of the biggest health problems that facing the world . And  the bladder cancer has a special place among the most spread cancers in Arab countries specially in Iraq and Egypt⁽²⁾ . It is one of the diseases which can be treated and cured if it is diagnosed early . This research is aimed at studying the assistant factors that diagnose bladder cancer such as (patient's age , gender , and other major complains of hematuria , burning or pain during urination and micturition disorders) and then determine which factors are the most effective in the possibility of diagnosing this disease by using the statistical model (logistic regression model) and depending on a random sample of (128) patients . After collecting and analyzing concerned collected data , the research concluded that the factor of (hematuria) has been found the most effective in the possibility of diagnosing this disease ,  followed by the factor (patient's age) . Other factors (gender , burning or pain during urination and micturition disorders) were found not significant effective in the possibility of diagnosing this disease . The research ended with some recommendations in this concern