Hierarcffical neural networks for censored data
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Date
2007-06
Authors
Ai Wern, Ooi
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Abstract
Although neural networks have been applied to survival analysis in recent years,
their use in survival analysis has been limited, especially when in the presence of
censored data. In this dissertation, a method for handling this problem is suggested. In
particular, a hierarchical neural network is proposed. To train the effectiveness of this
network. a data set consisting of 86 larynx cancer patients (Klein and Moeschberger,
1997) is used in the hierarchical neural networks and the nonhierarchical neural
networks. Some error measurements are utilized to compare the effectiveness among the
two models. The results show that the hierarchical model performs better than the
nonhierarchical model.
Description
Keywords
Neural networks , Censored data