Survival analysis with PyTorch
Project description
pycox is a python package for survival analysis and time-to-event prediction with PyTorch. It is built on the torchtuples package for training PyTorch models.
Read the documentation at: https://github.com/havakv/pycox
The package contains
- survival models: (Logistic-Hazard, DeepHit, DeepSurv, Cox-Time, MTLR, etc.)
- evaluation criteria (concordance, Brier score, Binomial log-likelihood, etc.)
- event-time datasets (SUPPORT, METABRIC, KKBox, etc)
- simulation studies
- illustrative examples
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
pycox-0.2.3.tar.gz
(57.8 kB
view details)
Built Distribution
pycox-0.2.3-py3-none-any.whl
(73.7 kB
view details)
File details
Details for the file pycox-0.2.3.tar.gz.
File metadata
- Download URL: pycox-0.2.3.tar.gz
- Upload date:
- Size: 57.8 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.7.1 importlib_metadata/4.10.0 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
c209c6b24d9262db7b8edb9a886b1a3bb73c9d6db9fb4559b5fb994e30743d6f
|
|
| MD5 |
ef98a10d80d5cdcf896f98f5f255f441
|
|
| BLAKE2b-256 |
b4bd6cd4cc35313b2d2c1d6b9c19486c6f706db64dbac8685b5c705d7e010d85
|
File details
Details for the file pycox-0.2.3-py3-none-any.whl.
File metadata
- Download URL: pycox-0.2.3-py3-none-any.whl
- Upload date:
- Size: 73.7 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/3.7.1 importlib_metadata/4.10.0 pkginfo/1.8.2 requests/2.27.1 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.9
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9ea3c64a4a650ccf6c96cf512712de330f2d75de32122d86995c7cd37ff105d1
|
|
| MD5 |
a98304bd776901b435cf6cccf37e444f
|
|
| BLAKE2b-256 |
01f65bce73f9c9aceddd06991fae39ac645f6376f860c7d35745968f7a2a2f1e
|
