TorchSurv: A Lightweight Package for Deep Survival Analysis
This provides a tool for researchers and practitioners in survival analysis to use flexible deep learning models, but it is incremental as it builds on existing PyTorch infrastructure.
The authors tackled the problem of implementing deep survival models in PyTorch by developing TorchSurv, a lightweight Python package that allows custom models without restrictive parametric forms, resulting in efficient implementation for high-dimensional data.
TorchSurv is a Python package that serves as a companion tool to perform deep survival modeling within the PyTorch environment. Unlike existing libraries that impose specific parametric forms, TorchSurv enables the use of custom PyTorch-based deep survival models. With its lightweight design, minimal input requirements, full PyTorch backend, and freedom from restrictive survival model parameterizations, TorchSurv facilitates efficient deep survival model implementation and is particularly beneficial for high-dimensional and complex input data scenarios.