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서지반출
Analysis of Feature Variables for Breast Cancer Diagnosis
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  • Analysis of Feature Variables for Breast Cancer Diagnosis
  • Analysis of Feature Variables for Breast Cancer Diagnosis
저자명
Jung. Yong Gyu,Kim. Jang Il,Sihn. Sung Chul,Heo. Jun
간행물명
Journal of Advanced Smart Convergence(JASC)
권/호정보
2013년|2권 2호|pp.36-39 (4 pages)
발행정보
한국인터넷방송통신학회
파일정보
정기간행물|ENG|
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기타
이 논문은 한국과학기술정보연구원과 논문 연계를 통해 무료로 제공되는 원문입니다.
서지반출

기타언어초록

It is becoming more important as the growing of health information and increasing in cancer patients diagnose over the time gradually. Among the various types of cancer, we focuses on breast cancer diagnosis. The accuracy of breast cancer diagnosis is increasing when the diagnosis is based on evidence and statistics. To do this we use the weka data mining tools and analysis algorithms significantly associated with the decision tree uses rules. In addition, the data pre-processing and cross-validation are used to increase the reliability of the results. The number and cause of the disease becomes important to increase evidence-based medical doctors. As the evidence-based medical, the data obtained from patients in the past through the disease by calculating the probability for future patients to diagnose and predict disease and treatment plan. It can be found by improving the survival rate plays an important role.