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# Deep survival analysis made easy
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> :warning::construction:**We are still working on the publication of this project and appreciate your patience until everything will be ready.**:construction::warning:
`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 on users, `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 survival model implementation, particularly beneficial for high-dimensional input data scenarios.
To build the documentation and for package development, please see [the development notes](https://opensource.nibr.com/torchsurv/devnotes.html) and
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[dev/environment.yml](dev/environment.yml).
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## Getting started
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We recommend starting with the [introductory guide](https://opensource.nibr.com/torchsurv/notebooks/introduction.html), where you'll find an overview of the package's functionalities.
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If you have any questions, suggestions, or feedback, feel free to reach out the developement team [us](https://opensource.nibr.com/torchsurv/AUTHORS.html).
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