| Summary: | 碩士 === 國立臺北科技大學 === 經營管理系碩士班 === 101 === In Taiwan, cancer stands as top one of the most lethal disease. Not only affect the quality of life of the patient and their families, but also cause a huge medical expenses and years of potential life lost. In order to reduce the incidence of cancer effectively, we try to find out the causes of low cancer rate by analyzing the pattern and availability of survival influence factors. The objective of this research is to investigate factors which influence survival time of cancer patients. Because survival time can be impacted by factors which are highly correlated with each other, to appropriate treatment of medical, the problem of multicollinearity must be solved. Therefore, this research proposes a new solution, Cox proportional hazards model combines independent component analysis method, to eliminate the multicollinearity among explanatory variables. To evaluate the performance of the proposed method relative to alternative approaches, we report one experiment study based on the dataset from Monte Carlo simulation experiments. The result shows that the proposed approach can solve the problem of multicollinearity and the significant effect between survival time and factors with cancer patients.
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