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Feed forward neural networks models for survival analysis

Artificial neural networks are increasingly being considered as an addition to the classical and modern statistical methods and have been found applications in a wide variety of medical problems. Due to their less restrictive framework that can incorporate nonlinearity and covariate interactions they have been proposed for the statistical analysis of censored survival data. This study presents different neural network strategies which have been suggested for modeling survival data.