FastCPH: Efficient Survival Analysis for Neural Networks. (arXiv:2208.09793v1 [stat.ML])

The Cox proportional hazards model is a canonical method in survival analysis
for prediction of the life expectancy of a patient given clinical or genetic
covariates -- it is a linear model in its original form. In recent years,
several methods have been proposed to generalize the Cox model to neural
networks, but none of these are both numerically correct and computationally
efficient. We propose FastCPH, a new method that runs in linear time and
supports both the standard Breslow …

analysis arxiv ml networks neural networks survival