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마이크로어레이 데이터와 임상인자의 통합데이터를 이용한 전립선암의 예후 예측
서보연(Boyeon Seo),윤영미(Youngmi Yoon) 한국정보기술학회 2012 한국정보기술학회논문지 Vol.10 No.5
Prognosis implies a medical prediction for the progress and development of disease. Prognosis prediction can dramatically improve the survival rate and quality of life since appropriate personalized treatment is possible. Recently for a prognosis prediction, microarry data which is gene expression information, has been used. This paper increased the classification accuracy of prognosis prediction by integrating gene expression information and clinical factors from clinical diagnosis. The experiments of this paper used microarray data of prostate cancer patients and clinical information data. This study compared and analyzed the results of 4 cases: gene expression data only, feature selected gene expression data, clinical factors only, and integrated data of 2nd and 3rd cases. In conclusion we were able to secure the highest prognosis prediction accuracy rate in the case of integrated data of gene expression data and clinical factors.