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Volumn 314, Issue , 2010, Pages 122-129

A clinical decision support system for breast cancer patients

Author keywords

Breast cancer; Decision support systems; Survival analysis

Indexed keywords

ARTIFICIAL NEURAL NETWORK; AUTOMATIC RELEVANCE DETERMINATION; BREAST CANCER; CLINICAL DECISION SUPPORT SYSTEMS; COX REGRESSION; GROUP ASSIGNMENTS; MEDICAL DATA; MISSING DATA; MODELLING METHODOLOGY; MULTIPLE IMPUTATION; REGRESSION TREES; SURVIVAL ANALYSIS; THREE MODELS;

EID: 77649244180     PISSN: 18684238     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-11628-5_13     Document Type: Article
Times cited : (6)

References (10)
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    • Clark, T.G.1    Altman, D.G.2
  • 5
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    • Computer Program to Assist in Making Decisions about Adjuvant Therapy for Women with Early Breast Cancer
    • Ravdin, P.M., Siminoff, L.A., Davis, G.J., Mercer, B.M., Hewlett, J., Gerson, N., Parker, H.L.: Computer Program to Assist in Making Decisions about Adjuvant Therapy for Women with Early Breast Cancer. J. Clin. Oncol. 74(4), 980-991 (2001)
    • (2001) J. Clin. Oncol , vol.74 , Issue.4 , pp. 980-991
    • Ravdin, P.M.1    Siminoff, L.A.2    Davis, G.J.3    Mercer, B.M.4    Hewlett, J.5    Gerson, N.6    Parker, H.L.7
  • 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
    • Lisboa, P.J.G., Wong, H., Harris, P., Swindell, R.: A Bayesian neural network approach for modelling censored data with an application to prognosis after surgery for breast cancer. Artificial Intelligence in Medicine 28(1), 1-25 (2003)
    • (2003) Artificial Intelligence in Medicine , vol.28 , Issue.1 , pp. 1-25
    • Lisboa, P.J.G.1    Wong, H.2    Harris, P.3    Swindell, R.4
  • 7
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    • Stratification methodologies for neural networks models of survival
    • Cabestany, J, et al, eds, IWANN 2009, Springer, Heidelberg
    • Fernandes, A.S., Etchells, T.A., Jarman, I.H., Fonseca, J.M.: Stratification methodologies for neural networks models of survival. In: Cabestany, J., et al. (eds.) IWANN 2009. LNCS, vol. 5517, pp. 989-996. Springer, Heidelberg (2009)
    • (2009) LNCS , vol.5517 , pp. 989-996
    • Fernandes, A.S.1    Etchells, T.A.2    Jarman, I.H.3    Fonseca, J.M.4
  • 9
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    • Etchells, T.A., Fernandes, A.S., Jarman, I.H., Fonseca, J.M., Lisboa, P.J.G.: Stratification of severity of illness indices: a case study for breast cancer prognosis. In: Lovrek, I., Howlett, R.J., Jain, L.C. (eds.) KES 2008, Part II. LNCS (LNAI), 5178, pp. 214-221. Springer, Heidelberg (2008)
    • Etchells, T.A., Fernandes, A.S., Jarman, I.H., Fonseca, J.M., Lisboa, P.J.G.: Stratification of severity of illness indices: a case study for breast cancer prognosis. In: Lovrek, I., Howlett, R.J., Jain, L.C. (eds.) KES 2008, Part II. LNCS (LNAI), vol. 5178, pp. 214-221. Springer, Heidelberg (2008)
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    • A review of evidence of health benefit from artificial neural networks in medical intervention
    • Lisboa, P.J.G.: A review of evidence of health benefit from artificial neural networks in medical intervention. Neural Networks 15(1), 9-37 (2002)
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    • Lisboa, P.J.G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.