DocumentCode
1553460
Title
On the use of artificial neural networks for the analysis of survival data
Author
Brown, Stephen F. ; Branford, Alan J. ; Moran, William
Author_Institution
Dept. of Math. & Stat., Flinders Univ. of South Australia, Bedford Park, SA, Australia
Volume
8
Issue
5
fYear
1997
fDate
9/1/1997 12:00:00 AM
Firstpage
1071
Lastpage
1077
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
Keywords
backpropagation; design of experiments; estimation theory; failure analysis; neural nets; probability; statistical analysis; backpropagation; failure time; neural networks; statistical analysis; survival data analysis; Artificial neural networks; Data analysis; Diseases; Independent component analysis; Neural networks; Particle measurements; Robustness; Statistical analysis; Statistics; Time measurement;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.623209
Filename
623209
Link To Document