지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
오류제보하기
Objectives: The purpose of this study was to specify major tongue diagnostic indicators and evaluate their significance in discriminating pattern identification subtypes in stroke patients.
Methods: This study used a community based multi-center observational design. Participants (n=1,502) were stroke patients admitted to 11 oriental medical university hospitals between December 2006 and February 2010. To determine which tongue indicator affected each pattern identification, a decision tree analysis of the chi-square automatic interaction detector (CHAID) algorithm was performed. The chi-squared test was used as the criterion in splitting data with a p-value less than 0.05 for division, which is the main procedure for developing a decision tree. The minimum sample size for each node was specified as n =10, and branching was limited to two levels.
Results: From the 9 tongue diagnostic indicators, 6 major tongue indicators (red tongue, pale tongue, yellow fur, white fur, thick fur, and teeth-marked tongue) were identified through the decision tree analysis. Furthermore, each pattern identification was composed of specific combinations of the 6 major tongue indicators.
Conclusions: This study suggests that the 6 tongue indicators identified through the decision tree analysis can be used to discriminate pattern identification subtypes in stroke patients. However, it is still necessary to re-evaluate other pattern identification indicators to further the objectivity and reliability of traditional Korean medicine.
Methods: This study used a community based multi-center observational design. Participants (n=1,502) were stroke patients admitted to 11 oriental medical university hospitals between December 2006 and February 2010. To determine which tongue indicator affected each pattern identification, a decision tree analysis of the chi-square automatic interaction detector (CHAID) algorithm was performed. The chi-squared test was used as the criterion in splitting data with a p-value less than 0.05 for division, which is the main procedure for developing a decision tree. The minimum sample size for each node was specified as n =10, and branching was limited to two levels.
Results: From the 9 tongue diagnostic indicators, 6 major tongue indicators (red tongue, pale tongue, yellow fur, white fur, thick fur, and teeth-marked tongue) were identified through the decision tree analysis. Furthermore, each pattern identification was composed of specific combinations of the 6 major tongue indicators.
Conclusions: This study suggests that the 6 tongue indicators identified through the decision tree analysis can be used to discriminate pattern identification subtypes in stroke patients. However, it is still necessary to re-evaluate other pattern identification indicators to further the objectivity and reliability of traditional Korean medicine.
목차
Introduction
Methods
Results
Discussion
References
참고문헌 (19)
참고문헌 신청
1. [단행본] - National Statistical Office in Korea / 2009 / Cause of death statistics in Korea / National Statistical Office in Korea
2. [학술지(정기간행물)] - Kim HJ / 2011 / Clinical approach to standardization of oriental medical diagnostic pattern identification in stroke patients / eCAM
3. [단행본] - Wiseman N / 1998 / A practical dictionary of Chinese medicine. Second edition / Paradigm Publications
4. [보고서] - / 2007 / WHO International Standard Terminologies on Traditional Medicine in the Western Pacific Region : 80 ~
5. [단행본] - Lee BK / 2004 / Traditional Korean medicine diagnostics. Sixth Edition / Seongbosa
2. [학술지(정기간행물)] - Kim HJ / 2011 / Clinical approach to standardization of oriental medical diagnostic pattern identification in stroke patients / eCAM
3. [단행본] - Wiseman N / 1998 / A practical dictionary of Chinese medicine. Second edition / Paradigm Publications
4. [보고서] - / 2007 / WHO International Standard Terminologies on Traditional Medicine in the Western Pacific Region : 80 ~
5. [단행본] - Lee BK / 2004 / Traditional Korean medicine diagnostics. Sixth Edition / Seongbosa
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UCI(KEPA) : I410-ECN-0101-2016-519-002228923