Statistics and Deep Belief Network-Based Cardiovascular Risk Prediction
활용도 Analysis
논문 Analysis
연구자 Analysis
저자
김재권
강운구
이영호
제어번호
104840413
학술지명
Healthcare Informatics Research
권호사항
Vol.
23
No.
3
[
2017
]
발행처
대한의료정보학회
발행처 URL
http://kosmi.org
자료유형
학술저널
수록면
169-175
(
7쪽)
언어
English
출판년도
2017
등재정보
KCI등재
판매처
'
Statistics and Deep Belief Network-Based Cardiovascular Risk Prediction' 의 참고문헌
한국인 남성에서 American Heart Association/National Heart, Lung, and Blood Institute와 International Diabetes Federation 대사증후군 진단 기준에 따른 심혈관질환 예측률의 비교
이도영
Diabetes and Metabolism Journal 32 4 317-327
[2008]
Using methods from the data-mining and machine-learning literature for disease classification and prediction : a case study examining classification of heart failure subtypes
Austin PC
J Clin Epidemiol 66 4 398-407
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Using deep learning to enhance cancer diagnosis and classification
Reducing the dimensionality of data with neural networks
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Technol Cancer Res Treat -
[2016]
Heart disease prediction system using data mining technique by fuzzy K-NN approach
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Tomar D
Int J Biosci Biotechnol 6 2 69-82
[2014]
Failure diagnosis using deep belief learning based health state classification
Deep belief network for clustering and classification of a continuous data
Context-dependent pre-trained deep neural networks for large-vocabulary speech recognition
Dahl GE
IEEE Trans Audio Speech Lang Process 20 1 30-42
[2012]
Breast cancer classification using deep belief networks
Ankle brachial index combined with Framingham Risk Score to predict cardiovascular events and mortality : a metaanalysis
Adaptive mining prediction model for content recommendation to coronary heart disease patients
Kim JK
Clust Comput 17 3 881-891
[2014]
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[2010]
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'
Statistics and Deep Belief Network-Based Cardiovascular Risk Prediction'
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