Analysis of in-Hospital Infection using J48 Tree and AD Tree

• 발행기관: 한국IT마케팅학회
• 저자명: 박재현(Jae Hyun Park) 이희석(Hee Seok Lee) 정용규(Yong Gyu Jung)
• 간행물 정보: 『The Journal of Information Technology and Management』Vol.3 No.1, 6~10쪽, 전체 5쪽
• 주제분류: 사회과학 > 무역학
• 파일형태: PDF
• 발행일자: 2015.03.30

영문 초록

In 21st century people are increased to look for hospital due to influenza, natural disasters for globally aging population. These hospitals are trying to prevent infection in preliminary research results, such as dropping the credibility and reputation of the hospital. In this paper, the data in the hospital onset CDI Community Onset and CLABSI Coronaty likely to be infected with a staff in the ICU figures are estimates at a university hospital in the United States. We try to analyze the data CLABSI Coronary ICU. CDI Community Onset was found to be almost endemic only about half less. Analysis of the data looked infections observed by comparing the difference between the actual number of infections observed and predicted. Predicted probability of CDI Community Onset is expected about 57%, CLABSI Coronary ICU was confirmed to be about 94%.

목차

Abstract

1. 서론

2. 문헌연구

3. 실험 및 실험결과

4. 결론

References

키워드

Clustering analysis in-hospital infections forecast accuracy Decision Tree J48 Tree AD Tree