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학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2017.7
- 수록면
- 169 - 175 (7page)
- DOI
- https://doi.org/10.4258/hir.2017.23.3.169
이용수
초록· 키워드
오류제보하기
Objectives: Cardiovascular predictions are related to patients’ quality of life and health. Therefore, a risk prediction model for cardiovascular conditions is needed. Methods: In this paper, we propose a cardiovascular disease prediction model using the sixth Korea National Health and Nutrition Examination Survey (KNHANES-VI) 2013 dataset to analyze cardiovascularrelated health data. First, statistical analysis was performed to find variables related to cardiovascular disease using health data related to cardiovascular disease. Second, a model of cardiovascular risk prediction by learning based on the deep belief network (DBN) was developed. Results: The proposed statistical DBN-based prediction model showed accuracy and an ROC curve of 83.9% and 0.790, respectively. Thus, the proposed statistical DBN performed better than other prediction algorithms.
Conclusions: The DBN proposed in this study appears to be effective in predicting cardiovascular risk and, in particular, is expected to be applicable to the prediction of cardiovascular disease in Koreans.
목차
등록된 정보가 없습니다.
참고문헌 (20)
참고문헌 신청
Austin PC / 2013 / Using methods from the data-mining and machine-learning literature for disease classification and prediction : a case study examining classification of heart failure subtypes / J Clin Epidemiol 66(4):398~407
송미화 / 2011 / A Multi-Classifier Based Guideline Sentence Classification System / Healthcare Informatics Research 17(4):224~231
Tomar D / 2014 / Feature selection based least square twin support vector machine for diagnosis of heart disease / Int J Biosci Biotechnol 6(2):69~82
Kim JK / 2016 / Improved prediction of the pathologic stage of patient with prostate cancer using the CART-PSO optimization analysis in the Korean population / Technol Cancer Res Treat
Khatibi V / 2010 / A fuzzy-evidential hybrid inference engine for coronary heart disease risk assessment / Expert Syst Appl 37(12):8536~8542
송미화 / 2011 / A Multi-Classifier Based Guideline Sentence Classification System / Healthcare Informatics Research 17(4):224~231
Tomar D / 2014 / Feature selection based least square twin support vector machine for diagnosis of heart disease / Int J Biosci Biotechnol 6(2):69~82
Kim JK / 2016 / Improved prediction of the pathologic stage of patient with prostate cancer using the CART-PSO optimization analysis in the Korean population / Technol Cancer Res Treat
Khatibi V / 2010 / A fuzzy-evidential hybrid inference engine for coronary heart disease risk assessment / Expert Syst Appl 37(12):8536~8542
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