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Volumn 2016-October, Issue , 2016, Pages 3321-3324

Multi-task transfer learning for in-hospital-death prediction of ICU patients

Author keywords

[No Author keywords available]

Indexed keywords

DECISION SUPPORT SYSTEM; FACTUAL DATABASE; HOSPITAL MORTALITY; HUMAN; INTENSIVE CARE; INTENSIVE CARE UNIT; LENGTH OF STAY; PROCEDURES; THEORETICAL MODEL;

EID: 85009084550     PISSN: 1557170X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EMBC.2016.7591438     Document Type: Conference Paper
Times cited : (6)

References (15)
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  • 2
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    • Saps 3 from evaluation of the patient to evaluation of the intensive care unit part 2 development of a prognostic model for hospital mortality at icu admission
    • R. P. Moreno, P. G. Metnitz, E. Almeida, B. Jordan, P. Bauer, R. A. Campos, G. Iapichino, D. Edbrooke, M. Capuzzo, J.-R. Le Gall et al., "Saps 3 from evaluation of the patient to evaluation of the intensive care unit part 2 development of a prognostic model for hospital mortality at icu admission," Intensive care medicine, vol. 31, no. 10, pp. 1345-1355, 2005
    • (2005) Intensive Care Medicine , vol.31 , Issue.10 , pp. 1345-1355
    • Moreno, R.P.1    Metnitz, P.G.2    Almeida, E.3    Jordan, B.4    Bauer, P.5    Campos, R.A.6    Iapichino, G.7    Edbrooke, D.8    Capuzzo, M.9    Le Gall, J.-R.10
  • 3
    • 33947137881 scopus 로고    scopus 로고
    • Assessing contemporary intensive care unit outcome: An updated mortality probability admission model (mpm0-III)
    • T. L. Higgins, D. Teres, W. S. Copes, B. H. Nathanson, M. Stark, and A. A. Kramer, "Assessing contemporary intensive care unit outcome: An updated mortality probability admission model (mpm0-iii)," Critical care medicine, vol. 35, no. 3, pp. 827-835, 2007
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  • 4
    • 85009067548 scopus 로고    scopus 로고
    • Predicting mortality of patients in intensive care: The physionet/computing in cardiology challenge 2012
    • I. Silva, G. B. Moody, D. J. Scott, L. A. Celi, and R. G. Mark, "Predicting mortality of patients in intensive care: The physionet/computing in cardiology challenge 2012," Computing in Cardiology. Krakow, 2012
    • (2012) Computing in Cardiology. Krakow
    • Silva, I.1    Moody, G.B.2    Scott, D.J.3    Celi, L.A.4    Mark, R.G.5
  • 6
    • 33746536145 scopus 로고    scopus 로고
    • Adaptation of maximum entropy capitalizer: Little data can help a lot
    • C. Chelba and A. Acero, "Adaptation of maximum entropy capitalizer: Little data can help a lot," Computer Speech & Language, vol. 20, no. 4, pp. 382-399, 2006
    • (2006) Computer Speech & Language , vol.20 , Issue.4 , pp. 382-399
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  • 10
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    • Convex multi-task feature learning
    • A. Argyriou, T. Evgeniou, and M. Pontil, "Convex multi-task feature learning," Machine Learning, vol. 73, no. 3, pp. 243-272, 2008
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  • 12
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    • A convex formulation for learning task relationships in multi-task learning
    • Y. Zhang and D.-Y. Yeung, "A convex formulation for learning task relationships in multi-task learning," in UAI, 2010, pp. 733-442
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.