On the use of artificial neural networks for the analysis of survival data

dc.contributor.author Brown, Stephen F.
dc.contributor.author Branford, Alan John
dc.contributor.author Moran, William
dc.date.accessioned 2011-12-06T03:50:14Z
dc.date.available 2011-12-06T03:50:14Z
dc.date.issued 1997
dc.description.abstract Artificial neural networks are a powerful tool for analyzing data sets where there are complicated nonlinear interactions between the measured inputs and the quantity to be predicted. We show that the results obtained when neural networks are applied to survival data depend critically on the treatment of censoring in the data. When the censoring is modeled correctly, neural networks are a robust model independent technique for the analysis of very large sets of survival data. en
dc.identifier.citation Brown, S., Branford, A. and Moran, W. 1997. On the use of artificial neural networks for the analysis of survival data. IEEE Transactions on Neural Networks, 8 (5), 1071-1077. en
dc.identifier.issn 1045-9227
dc.identifier.uri http://hdl.handle.net/2328/25778
dc.language.iso en
dc.publisher Institute of Electrical and Electronics Engineers Computer Society (IEEE Publishing) en
dc.rights.license In Copyright
dc.subject Statistics en
dc.subject Survival analysis en
dc.subject Neural network applications en
dc.subject Data analysis en
dc.title On the use of artificial neural networks for the analysis of survival data en
dc.type Article en
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