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Volumn , Issue , 2007, Pages 5420-5423

Continuous and discrete time survival analysis: Neural network approaches

Author keywords

[No Author keywords available]

Indexed keywords

CALIBRATION; DISCRIMINANT ANALYSIS; MATHEMATICAL MODELS;

EID: 57649201393     PISSN: 05891019     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2007.4353568     Document Type: Conference Paper
Times cited : (15)

References (15)
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    • Neural Networks as Statistical Methods in Survival Analysis
    • R. Dybowsky and V. Gant eds, Landes .Biosciences Publishers
    • B. D. Ripley, R. M. Ripley. "Neural Networks as Statistical Methods in Survival Analysis". Artificial Neural Networks: Prospects for Medicine (R. Dybowsky and V. Gant eds.), Landes .Biosciences Publishers, (1998).
    • (1998) Artificial Neural Networks: Prospects for Medicine
    • Ripley, B.D.1    Ripley, R.M.2
  • 3
    • 0034728368 scopus 로고    scopus 로고
    • On the misuses of artificial neural networks for prognostic and diagnostic classification in oncology
    • G. Schwarzer, W. Vach, M. Schumacher. "On the misuses of artificial neural networks for prognostic and diagnostic classification in oncology". Statistics in medicine 19, pp. 541-561, (2000).
    • (2000) Statistics in medicine , vol.19 , pp. 541-561
    • Schwarzer, G.1    Vach, W.2    Schumacher, M.3
  • 6
    • 0038162240 scopus 로고    scopus 로고
    • A Bayesian neural network approach for modelling censored data with an application to prognosis after surgery for breast cancer
    • P. J. G. Lisboa, H. Wong, P. Harris, R. Swindell. "A Bayesian neural network approach for modelling censored data with an application to prognosis after surgery for breast cancer". Artificial intelligence in medicine, 28, pp. 1-25, (2003).
    • (2003) Artificial intelligence in medicine , vol.28 , pp. 1-25
    • Lisboa, P.J.G.1    Wong, H.2    Harris, P.3    Swindell, R.4
  • 8
    • 0031921607 scopus 로고    scopus 로고
    • Feed forward neural networks for the analysis of censored survival data: A partial logistic regression approach
    • E. Biganzoli, P. Boracchi, L. Mariani, E. Marubini. "Feed forward neural networks for the analysis of censored survival data: a partial logistic regression approach". Statistics in Medicine. 17, pp. 1169-86, (1998).
    • (1998) Statistics in Medicine , vol.17 , pp. 1169-1186
    • Biganzoli, E.1    Boracchi, P.2    Mariani, L.3    Marubini, E.4
  • 10
    • 0000234257 scopus 로고
    • The evidence framework applied to classification networks
    • D. J. C. MacKay, "The evidence framework applied to classification networks". Neural Computation, 4 (5), pp. 720-36, (1992).
    • (1992) Neural Computation , vol.4 , Issue.5 , pp. 720-736
    • MacKay, D.J.C.1
  • 12
    • 0347724097 scopus 로고    scopus 로고
    • Modelling survival after treatment of intraocular melanoma using artificial neural networks and Bayes theorem
    • A. F. G. Taktak, A. C. Fisher, B. Damato, "Modelling survival after treatment of intraocular melanoma using artificial neural networks and Bayes theorem". Physics in Medicine and Biology. 49, pp. 87-98, (2004).
    • (2004) Physics in Medicine and Biology , vol.49 , pp. 87-98
    • Taktak, A.F.G.1    Fisher, A.C.2    Damato, B.3
  • 13
    • 0043126911 scopus 로고    scopus 로고
    • Logistic regression and artificial neural network classification models: A methodology review
    • S. Dreiseitl, L. Ohno-Machado. "Logistic regression and artificial neural network classification models: a methodology review". J.Biomed.Inform., vol. 35, no. 5-6, pp. 352-359, (2002).
    • (2002) J.Biomed.Inform , vol.35 , Issue.5-6 , pp. 352-359
    • Dreiseitl, S.1    Ohno-Machado, L.2
  • 14
  • 15
    • 0001668585 scopus 로고
    • Goodness-of-fit tests for randomly censored data
    • J. Koziol. "Goodness-of-fit tests for randomly censored data". Biometrika 67 (3), pp. 693-696, (1980).
    • (1980) Biometrika , vol.67 , Issue.3 , pp. 693-696
    • Koziol, J.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.