Skip to main content

Discrete-time competing risk analysis with neural networks

Project description

Documentation Status

Discotime: Discrete-time Competing Risks Models with PyTorch Lightning

Docs | Installation | Tutorial | Examples

Discotime is a python package for discrete-time survival analysis with neural networks that have been designed to handle competing risk models. The package relies on PyTorch Lightning to provide an easy-to-use interface, that still can be customized to your heart's content. The packages contains an implementation of discrete time-to-event models for neural networks (using PyTorch), different evaluation metrics, and a couple of different competing risk datasets.

The package is currently under development, Breaking changes are to be expected.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

discotime-0.0.4.tar.gz (24.6 kB view details)

Uploaded Source

File details

Details for the file discotime-0.0.4.tar.gz.

File metadata

  • Download URL: discotime-0.0.4.tar.gz
  • Upload date:
  • Size: 24.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.17

File hashes

Hashes for discotime-0.0.4.tar.gz
Algorithm Hash digest
SHA256 557bc866a821d9fb72dccee9f849062f5626126c0d273d4e50f517bf0affce64
MD5 b06a5d66140d37c71759994971a05977
BLAKE2b-256 1ddb74e9c7adf094b4bbed7671d4a89f7026854f7f771d14571bf47bef8ecb14

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page