DocumentCode
1928341
Title
Survival analysis and neural networks
Author
Eleuteri, Antonio ; Tagliaferri, Roberto ; Milano, L. ; Sansone, Gennaro ; D´Agostino, Diego ; De Placido, S. ; De Laurentiis, M.
Author_Institution
Dipt. di Matematica e Applicazioni, Naples Univ. Federico II, Italy
Volume
4
fYear
2003
fDate
20-24 July 2003
Firstpage
2631
Abstract
A feedforward neural network architecture for survival analysis is presented which generalizes the standard, usually linear, models described in literature. The time variable is embedded in the model and the network is able to extract its interactions with other system features. The resulting model is described in a hierarchical Bayesian framework. Experiments with synthetic and real world data show a comparison of this model with the standard ones.
Keywords
feedforward neural nets; medical computing; neural net architecture; probability; feedforward neural network architecture; hierarchical Bayesian framework; survival analysis; Bayesian methods; Context modeling; Data mining; Electronic circuits; Endocrine system; Failure analysis; Feedforward neural networks; Neural networks; Performance analysis; Predictive models;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2003. Proceedings of the International Joint Conference on
ISSN
1098-7576
Print_ISBN
0-7803-7898-9
Type
conf
DOI
10.1109/IJCNN.2003.1223982
Filename
1223982
Link To Document