561 387

Cited 0 times in

고혈압 관리를 위한 의사지원결정시스템의 데이터 마이닝 접근

Other Titles
 Data Mining Approach to Clinical Decision Support System for Hypertension Management 
Authors
 강석민  ;  조승연  ;  호승희  ;  김태수  ;  채영문 
Citation
 Journal of the Korean Society of Hypertension (대한고혈압학회지), Vol.9(2) : 133-143, 2003 
Journal Title
 Journal of the Korean Society of Hypertension (대한고혈압학회지) 
ISSN
 2233-8136 
Issue Date
2003
MeSH
Hypertension ; Data mining ; Decision support system
Keywords
Hypertension ; Data mining ; Decision support system
Abstract
Background: This study examined the utility of data mining algorithms for the management of hypertension. Methods: We studied 2,446 hospitalized patients with hypertension and 3,835 clinic patients with hypertension. Among data mining algorithms, we used clustering analysis and compared decision tree analysis with logistic regression. Results: On the contrary to the previous studies, decision tree performed better than logistic regression. We have also developed a CDSS (Clinical Decision Support System) with three modules (doctor, nurse, and patient) based on data warehouse architecture. Data warehouse collects and integrates relevant information from various databases from hospital information system. Conclusions: This study suggests that data mining algorithms may be an useful method for hypertension management and CDSS system can help improve decision making capability of doctors and improve accessibility of educational material for patients.
Files in This Item:
T200305748.pdf Download
DOI
OAK-2003-01038
Appears in Collections:
4. Graduate School of Public Health (보건대학원) > Graduate School of Public Health (보건대학원) > 1. Journal Papers
Yonsei Authors
Chae, Young Moon(채영문)
Ho, Seung Hee(호승희)
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/114198
사서에게 알리기
  feedback

qrcode

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse