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In cancer research, study of the hazard function provides useful information on the disease dynamic, in addition to the identification of prognostic factors. The widely utilized Cox proportional hazard model uses a stepwise nonparametric estimator for the baseline hazard function. Therefore the use of parametric models and/or other approaches to estimate the hazard function is often invoked. A recent...
Linear and non-linear flexible regression analysis techniques, such as those based on splines and feed forward artificial neural networks (FFANN), have been proposed for the statistical analysis of censored survival time data, to account for the presence of non linear effects of predictors. Among survival functions, the hazard has a biological interest for the study of the disease dynamics, moreover...
The affinity propagation algorithm is applied to a problem of breast cancer subtyping using traditional biologic markers. The algorithm provides a procedure to determine the number of profiles to be considered. A well know breast cancer case series was used to compare the results of the affinity propagation with the results obtained with standard algorithms and indexes for the optimal choice of the...
Clustering algorithms will, in general, either partition a given data set into a pre-specified number of clusters or will produce a hierarchy of clusters. In this paper we analyse several different clustering techniques and apply them to a particular data set of breast cancer data. When we do not know a priori which is the best number of groups, we use a range of different validity indices to test...
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