A novel neural network-based survival analysis model
作者： Antonio Eleuteri , Roberto Tagliaferri , Leopoldo Milano , Sabino De Placido , Michele De Laurentiis
DOI: 10.1016/S0893-6080(03)00098-4
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摘要: A feedforward neural network architecture aimed at survival probability estimation is presented which generalizes the standard, usually linear, models described in literature. The builds an approximation to of a system given time, conditional on features. resulting model hierarchical Bayesian framework. Experiments with synthetic and real world data compare performance this commonly used standard ones.
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