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Volumn , Issue , 2016, Pages 1273-1279

Learning adaptive forecasting models from irregularly sampled multivariate clinical data

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; DECISION MAKING; TIME SERIES;

EID: 85007158206     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (32)

References (31)
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    • The effects of the irregular sample and missing data in time series analysis
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    • Computational phenotype discovery using unsupervised feature learning over noisy, sparse, and irregular clinical data
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    • Clinical time series prediction with a hierarchical dynamical system
    • Springer
    • Liu, Z., and Hauskrecht, M. 2013. Clinical time series prediction with a hierarchical dynamical system. In Artificial Intelligence in Medicine. Springer. 227-237.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.