Earticle

초록

영어

Recent medical industry is an aging society and the application of national health insurance, with state-of-the-art research and development, including the pharmaceutical market is greatly increased. The nation's health care industry through new support expansion and improve the quality of life for the research and development will be needed. In addition, systemic administration of basic medical supplies , or drugs are needed , the drug at the same time managing how systematic analysis of pharmaceutical ingredients , based on data through the purchase of new medicines and pharmaceutical ingredients automatically classified by analyzing the statistics of drug purchases and the future a system that can predict a patient is needed. In this study, the drugs to the patient according to the component analysis and predictions for future research techniques, k-means clustering and k-NN (Nearest Neighbor) Comparative studies through experiments using the techniques employ a more efficient method to study how to proceed . In this study, the effects of the drugs according to the respective components in time according to the number of pieces in accordance with the patient by analyzing the statistics by predicting future patient better medical industry can be built.

목차

Abstract
 1. INTRODUCTION
 2. RELATED RESEARCH
  2.1 T2.1 K-MEANS Clustering
  2.2 k-NN (Nearest Neighbor)
 3. EXPERIMENT
 4. EXPERIMENTAL RESULT
 5. CONCLUSION
 REFERENCES

키워드

저자

• Jun Heo [ Dept. of Information and Communication, Kyungmin University, Korea ]
• Chae Yun Kim [ Dept. of Medical IT Marketing, Eulji University, Korea ]
• Yong-Gyu Jung [ Dept. of Medical IT Marketing, Eulji 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