Ranked designing of prognostic neural models for survival data

• Autorzy: Bobrowski L. , Krętowska M.
• Języki publikacji: EN

Abstrakty

EN

The procedure of designing the non-linear dependencies of survival time on a family of covariates is described in the paper. This dependence is treated as a prognostic model. The first stage of this procedure involves designing such layers of formal neurons which are ranked with respect to selected subsets of censored data. The model based on the hierarchical networks of formal neurons results in the piecewise constant dependence of the survival time on the covariates. The replacement of the formal neurons by the logistic ones made it possible transform this dependence into differentiable, regression-type function.

Słowa kluczowe

EN

neural networks; survival analysis; censored data; prognostic models

PL

biocybernetyka; inżynieria biomedyczna

• Wydawca: Nałęcz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences ; Elsevier
• Czasopismo: Biocybernetics and Biomedical Engineering
• Rocznik: 2002
• Tom: Vol. 22, no. 2-3
• Strony: 223--239
• Opis fizyczny: Bibliogr., rys., tab.

Twórcy

autor

Bobrowski L.

autor

Krętowska M.

• Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences, Warsaw, Poland,