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Volumn , Issue , 2012, Pages 173-178

Interval coded scoring systems for survival analysis

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BIOINFORMATICS; COMPLEX NETWORKS; NEURAL NETWORKS;

EID: 84877586944     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (5)

References (14)
  • 1
    • 16444374148 scopus 로고    scopus 로고
    • What makes a good clinical decision support system
    • G P Percell. What makes a good clinical decision support system. British Medical Journal, 330:740–741, 2005.
    • (2005) British Medical Journal , vol.330 , pp. 740-741
    • Percell, G.P.1
  • 2
    • 17144362818 scopus 로고    scopus 로고
    • Improving clinical practice using clinical decision support systems: A systematic review of trials to identify features critical to success
    • K Kawamoto, C A Houlihan, E A Balas, and D F Lobach. Improving clinical practice using clinical decision support systems: a systematic review of trials to identify features critical to success. British Medical Journal, 330:765–773, 2005.
    • (2005) British Medical Journal , vol.330 , pp. 765-773
    • Kawamoto, K.1    Houlihan, C.A.2    Balas, E.A.3    Lobach, D.F.4
  • 3
    • 67649603081 scopus 로고    scopus 로고
    • Improving medication use and outcomes with clinical decision support: A step-by-step guide
    • Chicago, IL
    • J A Osheroff. Improving medication use and outcomes with clinical decision support: a step-by-step guide. Healthcare Information and Management Systems Society, Chicago, IL, 2009.
    • (2009) Healthcare Information and Management Systems Society
    • Osheroff, J.A.1
  • 4
    • 2442682859 scopus 로고    scopus 로고
    • Presentation of multivariate data for clinical use: The framingham study risk score functions
    • L M Sullivan, J M Massaro, and R B D’Agostino. Presentation of multivariate data for clinical use: The framingham study risk score functions. Statistics in Medicine, 23(10):1631–1660, 2004.
    • (2004) Statistics in Medicine , vol.23 , Issue.10 , pp. 1631-1660
    • Sullivan, L.M.1    Massaro, J.M.2    D’Agostino, R.B.3
  • 6
    • 80052431188 scopus 로고    scopus 로고
    • Support vector methods for survival analysis: A comparison between ranking and regression approaches
    • V Van Belle, K Pelckmans, S Van Huffel, and J A K Suykens. Support vector methods for survival analysis: a comparison between ranking and regression approaches. Artificial Intelligence in Medicine, 53(2):107–118, 2011.
    • (2011) Artificial Intelligence in Medicine , vol.53 , Issue.2 , pp. 107-118
    • Van Belle, V.1    Pelckmans, K.2    Van Huffel, S.3    Suykens, J.A.4
  • 10
    • 44049111982 scopus 로고
    • Nonlinear total variation based noise removal algo- rithms
    • L I Rudin, S Osher, and E Fatemi. Nonlinear total variation based noise removal algo- rithms. Physica D: Nonlinear Phenomena, 60(1-4):259–268, 1992.
    • (1992) Physica D: Nonlinear Phenomena , vol.60 , Issue.1-4 , pp. 259-268
    • Rudin, L.I.1    Osher, S.2    Fatemi, E.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.