ETRI-Knowledge Sharing Plaform

ENGLISH

성과물

논문 검색
구분 SCI
연도 ~ 키워드

상세정보

학술지 A Novel Model for Metabolic Syndrome Risk Quantification Based on Areal Similarity Degree
Cited 16 time in scopus Download 1 time Share share facebook twitter linkedin kakaostory
저자
정상진, 조유미, 심상오, 최연정, 윤찬현
발행일
201403
출처
IEEE Transactions on Biomedical Engineering, v.61 no.3, pp.665-679
ISSN
0018-9294
출판사
IEEE
DOI
https://dx.doi.org/10.1109/TBME.2013.2286197
협약과제
14ME3700, 에너지 효율적인 네트워킹을 위한 단말 및 네트워크 제어?관리 기술 표준개발, 정상진
초록
Metabolic syndrome (MS) refers to a clustering of specific cardiovascular disease (CVD) risk factors whose underlying pathology is thought to be related to insulin resistance. The risk factors include insulin resistance, obesity, dyslipidemia, and hypertension and it is known to increase the risk for CVD and type II diabetes. Since MS helps to identify individuals at high risk for both CVD and type II diabetes, it has become a major public healthcare issue in many countries. There has been much effort to establish diagnostic criteria for MS, but the current diagnostic criteria of MS have weaknesses, such as binary decision based on diagnostic criteria, equal weight among risk factors, and difficulty in estimating the temporal progress of the risk factors. To resolve these problems, this paper proposes a risk quantification model for MS, which is based on areal similarity degree analysis between weighted radar charts comprising MS diagnostic criteria and examination results of risk factors. The clinical effectiveness of the proposed model is extensively evaluated by using data of a large number of subjects obtained from the third Korea National Health and Nutrition Examination Survey. The evaluation results show that the proposed model can quantify the risk of MS and effectively identify a group of subjects who might be classified into a potential risk group for having MS in the future. © 2013 IEEE.
키워드
Cardiovascular disease (CVD), chronic disease, healthcare, metabolic syndrome (MS), type II diabetes
KSP 제안 키워드
Cardiovascular diseases(CVD), Diagnostic Criteria, High risk, Metabolic syndrome, Novel model, Potential risk, Proposed model, Public healthcare, Radar chart, Risk Factors, Risk quantification