Earticle

초록

영어

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.

목차

Abstract
 1. INTRODUCTION
 2. NURTURE GAMES
  2.1 Decision Tree
  2.2 Association Rules
 3. EXPERIMENTS
  3.1 Data set
  3.2 Preprocessing
  3.3 Cross-validation
 4. EXPERIMENTAL RESULT
 5. CONCLUSIONS
 REFERENCES

키워드

저자

• Yong Gyu Jung [ Department of Medical IT Marketing, Eulji University, Korea ]
• Jang Il Kim [ Department of Medical IT Marketing, Eulji University, Korea ]
• Sung Chul Sihn [ Health Care Solutions Division, Fujitsu Korea Co. Ltd., Korea ]
• Jun Heo [ Dept. of Information and Communication, Kyungmin University, Korea ] corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  The International Journal of Advanced Smart Convergence

• 간기

  계간

• pISSN

  2288-2847

• eISSN

  2288-2855

• 수록기간

  2012~2025

• 십진분류

  KDC 326 DDC 380