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
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;
Conference_Titel :
Neural Networks, 2003. Proceedings of the International Joint Conference on
Print_ISBN :
0-7803-7898-9
DOI :
10.1109/IJCNN.2003.1223982
