Survival Analysis and Neural Networks

Antonio Eleuteri, Roberta Tagliaferri, Leopoldo Milano, Gennaro Sansone, Diego D'Agostino, Sabino De Placido, Michele De Laurentiis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
Pages2631-2636
Number of pages6
Volume4
Publication statusPublished - 2003
EventInternational Joint Conference on Neural Networks 2003 - Portland, OR, United States
Duration: Jul 20 2003Jul 24 2003

Other

OtherInternational Joint Conference on Neural Networks 2003
Country/TerritoryUnited States
CityPortland, OR
Period7/20/037/24/03

ASJC Scopus subject areas

  • Software

Fingerprint

Dive into the research topics of 'Survival Analysis and Neural Networks'. Together they form a unique fingerprint.

Cite this