Earticle

초록

영어

Recently, the clinical and healthcare recommending service is required in medical center for the clinical diagnosis and plan of treatment in connection with cardiovascula disease. We propose a method of the clinical and healthcare recommending service based on cardiovascula disease pattern analysis for medical treatment service. We use SVM(Support Vector Machine) to segment the clinical historical data, to join patients’ clinical test data with input vectors of multi-parametric features, cardiovascula disease code, input factors and finally forms clusters of the clinical historical data based on electronic medical record. Then, we make an application on the clinical and healthcare recommending service for cardiovascula disease treatment information of cardiovascula patients to reduce patients’ search effort to get the curing information and the diagnosis for recovering their health, to improve the accuracy for the clinical and healthcare recommending service. We carry out experiments with data set of medical center to measure its performance. We report some of the experimental results.

목차

Abstract
 1. Introduction
 2. Cardiovascula Disease Pattern Analysis For Clinical and Healthcare Recommending Service
  2.1. Application for Predictive Pattern Analysis using SVM to Segment the Clinical Historical Data 
  2.2. Clinical and Healthcare Recommending Service for Medical Treatment Service
 3. Experimental Result
  3.1. Experimental Data for Evaluation
  3.2. Experiment and Evaluation
 4. Conclusion
 Acknowledgments
 References

키워드

저자

• Young Sung Cho [ Database and Bioinformatics Laboratory, School of Electrical and Computer Engineering, Chungbuk National University ]
• Song Chul Moon [ Department of Computer Science, Namseoul University ]
• Kwang Sun Ryu [ Database and Bioinformatics Laboratory, School of Electrical and Computer Engineering, Chungbuk National University ]
• Keun Ho Ryu [ Database and Bioinformatics Laboratory, School of Electrical and Computer Engineering, Chungbuk National University ] Corresponding author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605